Databases / Data management Books
Chapman and Hall/CRC Data Stewardship for Open Science
Book SynopsisData Stewardship for Open Science: Implementing FAIR Principles has been written with the intention of making scientists, funders, and innovators in all disciplines and stages of their professional activities broadly aware of the need, complexity, and challenges associated with open science, modern science communication, and data stewardship. The FAIR principles are used as a guide throughout the text, and this book should leave experimentalists consciously incompetent about data stewardship and motivated to respect data stewards as representatives of a new profession, while possibly motivating others to consider a career in the field. The ebook, avalable for no additional cost when you buy the paperback, will be updated every 6 months on average (providing that significant updates are needed or avaialble). Readers will have the opportunity to contribute material towards these updates, and to develop their own data management plans, via the free Data Stewardship Wizard.
£48.44
Taylor & Francis Inc The Human Element of Big Data
Book SynopsisThe proposed book talks about the participation of human in Big Data.How human as a component of system can help in making the decision process easier and vibrant.It studies the basic build structure for big data and also includes advanced research topics.In the field of Biological sciences, it comprises genomic and proteomic data also. The book swaps traditional data management techniques with more robust and vibrant methodologies that focus on current requirement and demand through human computer interfacing in order to cope up with present business demand. Overall, the book is divided in to five parts where each part contains 4-5 chapters on versatile domain with human side of Big Data.Table of ContentsPrefaceEditorsContributorsSection I Introduction to the Human Element of Big Data: Definition, New Trends, and Methodologies1 Taming the Realm of Big Data Analytics: Acclamation or Disaffection?Audrey Depeige2 Fast Data Analytics Stack for Big Data AnalyticsSourav Mazumder3 Analytical Approach for Big Data in the Internet of ThingsAnand Paul, Awais Ahmad, and M. Mazhar Rathore4 Analysis of Costing Issues in Big DataKuldeep Singh Jadon and Radhakishan YadavSection II Algorithms and Applications of Advancement in Big Data5 An Analysis of Algorithmic Capability and Organizational ImpactGeorge Papachristos and Scott W. Cunningham6 Big Data and Its Impact on Enterprise ArchitectureMeena Jha, Sanjay Jha, and Liam O’Brien7 Supportive Architectural Analysis for Big DataUtkarsh Sharma and Robin Singh Bhadoria8 Clustering Algorithms for Big Data: A SurveyAnkita Sinha and Prasanta K. JanaSection III Future Research and Scope for the Human Element of Big Data9 Smart Everything: Opportunities, Challenges, and ImpactSiddhartha Duggirala10 Social Media and Big DataRichard Millham and Surendra Thakur11 Big Data Integration, Privacy, and SecurityRafael Souza and Chandrakant Patil12 Paradigm Shifts from E-Governance to S-GovernanceAkshi Kumar and Abhilasha SharmaSection IV Case Studies for the Human Element of Big Data: Analytics and Performance13 Interactive Visual Analysis of Traffic Big DataZhihan Lv, Xiaoming Li, Weixi Wang, Jinxing Hu, and Ling Yin14 Prospect of Big Data Technologies in HealthcareRaghavendra Kankanady and Marilyn Wells15 Big Data Suite for Market Prediction and Reducing Complexity Using Bloom FilterMayank Bhushan, Apoorva Gupta, and Sumit Kumar Yadav16 Big Data Architecture for Climate Change and Disease DynamicsDaphne Lopez and Gunasekaran ManogaranIndex
£114.00
Taylor & Francis Inc Data Mining
Book SynopsisData Mining: A Tutorial-Based Primer, Second Edition provides a comprehensive introduction to data mining with a focus on model building and testing, as well as on interpreting and validating results. The text guides students to understand how data mining can be employed to solve real problems and recognize whether a data mining solution is a feasible alternative for a specific problem. Fundamental data mining strategies, techniques, and evaluation methods are presented and implemented with the help of two well-known software tools. Several new topics have been added to the second edition including an introduction to Big Data and data analytics, ROC curves, Pareto lift charts, methods for handling large-sized, streaming and imbalanced data, support vector machines, and extended coverage of textual data mining. The second edition contains tutorials for attribute selection, dealing with imbalanced data, outlier analysis, time series analysis, mining textual data, and morTrade Review"Dr. Roiger does an excellent job of describing in step by step detail formulae involved in various data mining algorithms, along with illustrations. In addition, his tutorials in Weka software provide excellent grounding for students in comprehending the underpinnings of Machine Learning as applied to Data Mining. The inclusion of RapidMiner software tutorials and examples in the book is also a definite plus since it is one of the most popular Data Mining software platforms in use today."--Robert Hughes, Golden Gate University, San Francisco, CA, USATable of ContentsData Mining: A First View. Data Mining: A Closer Look. Basic Data Mining Techniques. Weka – A Tool for Knowledge Discovery.Pre Processing & Visualization Techniques. Knowledge Discovery in Databases. Formal Evaluation Techniques. The DataWarehouse. Neural Networks. Building Neural Networks with BpKNet. Statistical Methods. Specialized Techniques. A Case Studyin Knowledge Discovery. Rule-Based Systems. Managing Uncertainty in Rule-Based Systems. Intelligent Agents
£59.84
Taylor & Francis Inc Big Data Management and Processing
Book SynopsisFrom the Foreword:Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies.---Sartaj Sahni, University of Florida, USABig Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seaTable of ContentsBig Data Management. Big Data Design, implementation, evaluation and services. Big Data as integration of technologies. Big Data analytics and visualization. Query processing and indexing. Elasticity for data management systems. Self-adaptive and energy-efficient mechanisms. Performance evaluation. Security, privacy, trust, data ownership and risk simulations. Processing. Techniques, algorithms and innovative methods of processing. Business and economic models. Adoption cases, frameworks and user evaluations. Data-intensive and scalable computing on hybrid infrastructures. MapReduce based computations. Many-Task Computing in the Cloud. Streaming and real-time processing. Big Data systems and applications for multidisciplinary applications.
£117.00
Taylor & Francis Inc The Analytics Process
Book SynopsisThis book is about the process of using analytics and the capabilities of analytics in today's organizations. Cutting through the buzz surrounding the term analytics and the overloaded expectations about using analytics, the book demystifies analytics with an in-depth examination of concepts grounded in operations research and management science. Analytics as a set of tools and processes is only as effective as: The data with which it is working The human judgment applying the processes and understanding the output of these processes. For this reason, the book focuses on the analytics process. What is intrinsic to analytics' real organizational impact are the careful application of tools and the thoughtful application of their outcomes. This work emphasizes analytics as part of a process that supports decision-making within organizations. It wants to debunk overblown expectations that somehow analytics outputs or analytics as applied toTable of ContentsSECTION I. ANALYTICS PROCESS CONCEPTS. About the Analytics Process. Illustrating the Analytics Process through Risk Assessment. and Modeling. Analytics, Strategy, and Management Control Systems. SECTION II. ANALYTICS PROCESS APPLICATIONS. Data, Information, and Intelligence. The Rise of Big Data and Analytics in Higher Education. Google Analytics as a Prosumption Tool for Web Analytics. Knowledge-Based Cause–Effect Analysis Enriched by Generating Multilayered DSS Models. Online Community Projects in Lithuania: Cyber Security Perspective. Exploring Analytics in Health Information Delivery to Acute Health Care in Australia. Information Visualization and Knowledge Reconstruction of RFID Technology Translation in Australian Hospitals. Health Care Analytics and Big Data Management in Influenza Vaccination Programs: Use of Information–Entropy Approach. Sharing Knowledge or Just Sharing Data? Index.
£114.00
Taylor & Francis Inc Advances in Smart Cities
Book SynopsisThis is an edited book based on the selected submissions made to the conference titled International Conference in Smart Cities. The project provides an innovative and new approach to holistic management of cities physical, socio-economic, environmental, transportation and political assets across all domains, typically supported by ICT and open data.Table of ContentsAdoption and Acceptance of Mandatory Electronic Public Services by Citizens in the Developing World. Self-Sustainable Integrated Township. Smart People for Smart Cities. How Smart Cities influence Governance? Role of Manufacturing Sector to Develop Smart Economy. Concept of Smart Village in India. Smart City. Smart City Technologies. A Cloud-Based Mobile Application for Cashless Payments. Financial Viability of Energy Conservation using Natural Light. Information Risk for Digital Services. Mobile Commerce Research for Individual, Business and Society. The Shift Toward a Sustainable Urban Mobility through Decision Support Systems.
£133.00
Microsoft Press,U.S. Tabular Modeling in Microsoft SQL Server Analysis
Book SynopsisWith SQL Server Analysis Services 2016, Microsoft has dramatically upgraded its Tabular approach to business intelligence data modeling, making Tabular the easiest and best solution for most new projects. In this book, two world-renowned experts in Microsoft data modeling and analysis cover all you need to know to create complete BI solutions with these powerful new tools. Marco Russo and Alberto Ferrari walk you step-by-step through creating powerful data models, and then illuminate advanced features such as optimization, deployment, and scalability. Tabular Modeling in Microsoft SQL Server Analysis Services will be indispensable for everyone moving to Analysis Services Tabular, regardless of their previous experience with tabular-style models or with Microsoft's older Analysis Services offerings. It will also be an essential follow-up for every reader of the authors' highly-praised Microsoft SQL Server 2012 Analysis Services: The BISM Tabular Model.Table of Contents CHAPTER 1 Introducing the tabular model CHAPTER 2 Getting started with the tabular model CHAPTER 3 Loading data inside Tabular CHAPTER 4 Introducing calculations in DAX CHAPTER 5 Building hierarchies CHAPTER 6 Data modeling in Tabular CHAPTER 7 Tabular Model Scripting Language (TMSL) CHAPTER 8 The tabular presentation layer CHAPTER 9 Using DirectQuery CHAPTER 10 Security CHAPTER 11 Processing and partitioning tabular models CHAPTER 12 Inside VertiPaq CHAPTER 13 Interfacing with Tabular CHAPTER 14 Monitoring and tuning a Tabular service CHAPTER 15 Optimizing tabular models CHAPTER 16 Choosing hardware and virtualization
£33.37
Microsoft Press,U.S. MCSA SQL Server 2016 Database Development Exam
Book Synopsis
£43.19
Microsoft Press,U.S. Exam Ref 70-764 Administering a SQL Database
Book SynopsisPrepare for Microsoft Exam 70-764—and help demonstrate your real-world mastery of skills for database administration. This exam is intended for database administrators charged with installation, maintenance, and configuration tasks. Their responsibilities also include setting up database systems, making sure those systems operate efficiently, and regularly storing, backing up, and securing data from unauthorized access. Focus on the expertise measured by these objectives: • Configure data access and auditing • Manage backup and restore of databases • Manage and monitor SQL Server instances • Manage high availability and disaster recovery This Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you have working knowledge of database installation, configuration, and maintenance tasks. You should also have experience with setting up database systems, ensuring those systems operate efficiently, regularly storing and backing up data, and securing data from unauthorized access. About the Exam Exam 70-764 focuses on skills and knowledge required for database administration. About Microsoft Certification Passing both Exam 70-764 and Exam 70-765 (Provisioning SQL Databases) earns you credit toward an MCSA: SQL 2016 Database Administration certification. See full details at: microsoft.com/learning Table of Contents 1. Configure Data Access and Auditing 2. Manage Backup and Restore of Databases 3. Manage and Monitor SQL Server Instances 4. Manage High Availability and Disaster Recovery
£23.59
Microsoft Press,U.S. Exam Ref 70-761 Querying Data with Transact-SQL
Book SynopsisPrepare for Microsoft Exam 70-761–and help demonstrate your real-world mastery of SQL Server 2016 Transact-SQL data management, queries, and database programming. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical-thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: • Filter, sort, join, aggregate, and modify data • Use subqueries, table expressions, grouping sets, and pivoting • Query temporal and non-relational data, and output XML or JSON • Create views, user-defined functions, and stored procedures • Implement error handling, transactions, data types, and nulls This Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you have experience working with SQL Server as a database administrator, system engineer, or developer • Includes downloadable sample database and code for SQL Server 2016 SP1 (or later) and Azure SQL Database Querying Data with Transact-SQL About the Exam Exam 70-761 focuses on the skills and knowledge necessary to manage and query data and to program databases with Transact-SQL in SQL Server 2016. About Microsoft Certification Passing this exam earns you credit toward a Microsoft Certified Solutions Associate (MCSA) certification that demonstrates your mastery of essential skills for building and implementing on-premises and cloud-based databases across organizations. Exam 70-762 (Developing SQL Databases) is also required for MCSA: SQL 2016 Database Development certification. See full details at: microsoft.com/learningTable of ContentsCHAPTER 1 Manage data with Transact-SQL CHAPTER 2 Query data with advanced Transact-SQL components CHAPTER 3 Program databases by using Transact-SQL
£23.59
Oryx Press Inc Thesaurus of ERIC Descriptors, 14th Edition
£109.00
Artech House Publishers Knowledge Management in the Intelligence Enterprise
Book SynopsisThis system-level resource specifically applies knowledge management principles, practices and technologies to the intelligence domain. Designed for those responsible for the management of an intelligence enterprise operation and its delivery of reliable intelligence to key decision-makers, the text describes the essential principles of intelligence, from collection, processing and analysis to dissemination, for both national intelligence and business applications. The author aims to provide a balanced treatment of the organizational and architectural components of knowledge management, offering an understanding of the system infrastructure, tools and technologies necessary to implement the intelligence enterprise. He explores real-world applications and presents a detailed example of competitive intelligence unit design. Including over 80 illustrations, the volume offers a practical description of enterprise architecture design methodology, and covers the full range of national, military, business and competitive intelligence.Table of ContentsKnowledge management and intelligence; the intelligence enterprise; knowledge management processes; the knowledge-based intelligence organization; intelligence analysis and synthesis; implementing analysis-synthesis; knowledge internalization and externalization; explicit knowledge combination and transformation; the intelligence enterprise architecture; knowledge management technologies.
£118.25
MC Press, LLC DB2 9 for z/OS Database Administration:
Book SynopsisIn order to become an IBM Certified Database Administrator - DB2 9 DBA for z/OS, you must pass two exams: DB2 9 Fundamentals Exam (Exam 730), and DB2 9 Database Administrator for z/OS (Exam 732)—the primary focus focus of this book.Written by two members of the team who participated in the actual writing of the exam, this specialized study guide covers every topic that you will need to know to pass Exam 732, including database design and implementation, operation and recovery, security and auditing, performance, as well as installation and migration/upgrade. But that is only the beginning. It also covers the new features of DB2 9 for both database and application development.This comprehensive guide includes an extensive set of practice questions in each chapter that closely model the actual exam, along with an answer key with a description of why the answer is the correct one. No other source gives you this much help in passing the exam.Whether you plan to take Exam 732 or just want to master the skills needed to be an effective database administrator on z/OS systems, this is the only book you’ll need.With the DB2 9 for z/OS Database Administration Certification Study Guide, you will:• Discover the changes to DB2 9 that you’ll need to know in order to be successful when taking the exam • Learn how to effectively administer a DB2 database • Receive an explanation of every objective included on the test…by someone involved in the creation of the actual exam • Find 85 practice questions based on the actual exam’s format and approach, along with comprehensive answers to help you gain understandingPublisher’s Note: While this book covers much of the information needed to prepare for Exam 730, a far more in-depth review of topics specifically related to Exam 730 can be found in the MC Press companion book: DB2 9 Fundamentals Certification Study Guide by Roger E. Sanders.Table of ContentsDB2 Product Fundamentals Environment Access and Security Database Objects Retrieving and Manipulating Database Objects Advanced SQL Coding Maintaining Data Recovery and Restart Data Sharing Using SQL in an Application Pogram Binding an Application Program Application Program Features Stored Procedures Accessing Distributed Data Advanced Functionality Locking and Concurrency Performance Monitoring and Tuning
£54.15
MC Press, LLC DB2 9 for Linux, UNIX, and Windows Database
Book SynopsisIn DB2 9 for Linux, UNIX, and Windows Database Administration Upgrade Certification Study Guide , Roger E. Sanders--one of the world's leading DB2 authors and an active participant in the development of IBM's DB2 certification exams--covers everything a reader needs to know to pass the short--but notoriously challenging--DB2 9 for LUW DBA Certification Upgrade exam (Exam 736). This specialized study guide steps you through all of the topics that are covered on the exam, including server management, data placement, XML concepts, activity analysis, high availability, database security, and much more. Everything new to DB2 9 that you will need to know in order to successfully pass the exam is covered in this book. Taking and passing the DB2 9 for LUW DBA Certification Upgrade exam (Exam 736) provides validation that you have mastered DB2 9. Passing this exam also earns you the IBM Certified Database Administrator or Advanced Database Administrator certification. This concentrated guide includes an extensive set of practice questions in each chapter that closely models the actual exam, along with an answer key with a full description of why the answer is the correct one. No other source gives you this much help in passing the exam. With the DB2 9 for Linux, UNIX, and Windows Database Administration Upgrade Certification Study Guide , you will: Gain the knowledge necessary to pass the DB2 9 for LUW DBA Upgrade Certification exam (Exam 736) Discover the changes to DB2 9 that you'll need to know in order to be successful when taking the exam Receive an explanation of every topic included on the test...by someone involved in the creation of the actual exam Find 60 practice questions based on the actual exam's format and approach, along with comprehensive answers to the test questions to help you gain understandingTable of ContentsChapter 1: IBM DB2 9 Certification Chapter 2: Server Management Chapter 3: Data Placement Chapter 4: XML Concepts Chapter 5: Analyzing DB2 Activity Chapter 6: High Availability Chapter 7: Security
£29.40
MC Press, LLC DB2 9 for Linux, UNIX, and Windows Advanced
Book SynopsisDatabase administrators versed in DB2 wanting to learn more about advanced database administration activities and students wishing to gain knowledge to help them pass the DB2 9 UDB Advanced DBA certification exam will find this exhaustive reference invaluable. Written by two individuals who were part of the team that developed the certification exam, this comprehensive study guide prepares the student for challenging questions on database design; data partitioning and clustering; high availability diagnostics; performance and scalability; security and encryption; connectivity and networking; and much more. Providing sample questions in each chapter, a complete practice test modeled after the actual exam, and an extensive answer key providing full explanations for each correct answer, readers will find this to be a key resource in stimulating the learning process.Table of ContentsIBM DB2 9 Certification Database Design Data Partitioning and Clustering High Availability and Diagnosis Performance and Scalability Security Connectivity and Networking
£54.15
MC Press, LLC Customer Experience Analytics: The Key to
Book SynopsisThrough a series of case studies from a variety of industries to show how customer experience analytics (CEA) is reshaping business, this book explores the technologies available to help businesses create a competitive advantage and real-time relationship with customers. This book provides a program based in business values that appeal to senior management and a solution architecture that utilizes the fast, intelligent, and productive capabilities of CEA. Exploring the internet's impact on consumer power, this book reflects on the sophistication of business markets in multisupplier management, electronic gateways, and customer and product data across the supply hierarchy.
£17.95
MC Press, LLC DB2 10 for z/OS: Cost Savings . . . Right Out of
Book SynopsisProviding expert knowledge about the features in the new release of DB2 for z/OS, this extensive guide details the innovations of DB2 10’s SQL and pureXML enhancements—which increase productivity, enhance performance, and simplify application ports. DB2 for z/OS continues to be the undisputed leader in total system availability, scalability, security, and reliability at the lowest cost per transaction. This resource focuses on the features and functions of DB2 10 for IT, including improving operational efficiencies and reducing costs, as well as covering innovations in resiliency for business-critical information, rapid application and warehouse deployment for business growth, and enhanced business analytics and mathematical functions with QMF.
£17.95
MC Press, LLC DB2 9.7 for Linux, UNIX, and Windows Database
Book SynopsisThe relational database-management system DB2 9.7 is given detailed and comprehensive treatment in this exam-preparation resource. Compiled from presentation material used in the popular “Crammer Course” at the IBM Information On Demand Conference, everything required for certification is presented here, including server management, design, business rules implementation, activity monitoring, security, and networking. An essential resource, this guide is helpful when studying to pass the official DB2 9.7 for LUW DBA certification exam.
£19.95
MC Press, LLC DB2 10.1/10.5 for Linux, UNIX, and Windows
Book SynopsisMuch more than a simple certification study aid, this comprehensive 1,248 page book is designed to help you master all aspects of IBM DB2 database administration and prepare you to take and pass IBM's Certification Exams 611 and 311: Certified Database Administrator. Building on years of extensive hands-on experience, the authors step you through all the areas covered on the test. The book dives deep inside each certification topic: DB2 server management, physical design, business rules implementation, activity monitoring, utilities, high availability, security, and connectivity and networking. There is even a "crash course" chapter on DB2 10.5 features. Each chapter includes an extensive set of practice questions along with carefully explained answers. This book provides more than 400 practice questions and answers, more than 120 "flash cards" to help you study for the exam, and 50 step-by-step DB2 feature implementation procedures.Trade Review"This resource is designed to give the DB2 professional the information required in order to successfully obtain certification, or even to simply enhance their existing scope of DB2 knowledge. The authors have done an excellent job of distilling their many years of experience, both within the lab environment and within the live production environment into a logical, well-organized reference. Each section contains the fundamentals, plus valuable insights from the authors, and is backed up with sample exam questions, as well as detailed answers . . . . I am confident that with this guide, your certification will not be far away!" Eric Sheley, Global IT Director, FTSE 100 Global Consumer Goods Company
£94.40
MC Press, LLC The Business Value of DB2 for z/OS: IBM DB2
Book SynopsisCelebrating the 30th anniversary of the first release of DB2, this book highlights the important milestones, capabilities, and impacts of the database management software for IBM s mainframe operating system. Special focus is given to IBM DB2 Analytics Accelerator, covering the key design and operational aspects that enable IBM DB2 for z/OS clients to benefit from faster performance, reduced CPU usage, and lower costs. The second half of the book discusses performance enhancements and cost-saving measures in the version 10 release and is rich with hints and tips for a successful upgrade. A special section on query performance and IBM DB2 Optimizer illustrates how DB2 10 addresses customer issues such as reducing total cost of ownership while maintaining stability and reliability. The final section is a collection of case studies in which DB2 10 for z/OS customers share their migration experiences and articulate the business benefits they are seeing since upgrading to the new release.
£13.49
MC Press, LLC DB2 10.5 DBA for LUW Upgrade from DB2 10.1:
Book SynopsisRoger E. Sanders, a leading DB2 author and an active participant in the development of DB2 certification exams, covers everything a reader needs to know to take and pass the DB2 10.5 DBA for LUW Upgrade from DB2 10.1 certification exam. This set of study notes takes the reader through each of the topics: DB2 server management; physical design; monitoring DB2 activity; high availability; and utilities. In addition, this book contains a complete practice exam with 60 questions, which closely models the actual 311 exam, along with a detailed answer key.
£17.95
Pearson Education (US) CCNA Cybersecurity Operations Course Booklet
Book SynopsisYour Cisco Networking Academy Course Booklet is designed as a study resource you can easily read, highlight, and review on the go, wherever the Internet is not available or practical: · The text is extracted directly, word-for-word, from the online course so you can highlight important points and take notes in the “Your Chapter Notes” section. · Headings with the exact page correlations provide a quick reference to the online course for your classroom discussions and exam preparation. · An icon system directs you to the online curriculum to take full advantage of the images embedded within the Networking Academy online course interface and reminds you to perform the labs, Class Activities, interactive activities, Packet Tracer activities, watch videos, and take the chapter quizzes and exams. The Course Booklet is a basic, economical paper-based resource to help you succeed with the Cisco Networking Academy online course. Table of ContentsChapter 0 Course Introduction 1 0.0 Welcome to CCNA: Cybersecurity Operations 1 0.0.1 Message to the Student 1 Chapter 1 Cybersecurity and the Security Operations Center 5 1.0 Introduction 5 1.1 The Danger 5 1.1.1 War Stories 5 1.1.1.1 Hijacked People 5 1.1.1.2 Ransomed Companies 5 1.1.1.3 Targeted Nations 6 1.1.1.4 Lab - Installing the CyberOps Workstation Virtual Machine 6 1.1.1.5 Lab - Cybersecurity Case Studies 6 1.1.2 Threat Actors 6 1.1.2.1 Amateurs 6 1.1.2.2 Hacktivists 7 1.1.2.3 Financial Gain 7 1.1.2.4 Trade Secrets and Global Politics 7 1.1.2.5 How Secure is the Internet of Things? 7 1.1.2.6 Lab - Learning the Details of Attacks 7 1.1.3 Threat Impact 8 1.1.3.1 PII and PHI 8 1.1.3.2 Lost Competitive Advantage 8 1.1.3.3 Politics and National Security 8 1.1.3.4 Lab - Visualizing the Black Hats 9 1.2 Fighters in the War Against Cybercrime 9 1.2.1 The Modern Security Operations Center 9 1.2.1.1 Elements of a SOC 9 1.2.1.2 People in the SOC 9 1.2.1.3 Process in the SOC 10 1.2.1.4 Technologies in the SOC 10 1.2.1.5 Enterprise and Managed Security 10 1.2.1.6 Security vs. Availability 11 1.2.1.7 Activity - Identify the SOC Terminology 11 1.2.2 Becoming a Defender 11 1.2.2.1 Certifications 11 1.2.2.2 Further Education 12 1.2.2.3 Sources of Career Information 12 1.2.2.4 Getting Experience 13 1.2.2.5 Lab - Becoming a Defender 13 1.3 Summary 13 Chapter 2 Windows Operating System 17 2.0 Introduction 17 2.1 Windows Overview 17 2.1.1 Windows History 17 2.1.1.1 Disk Operating System 17 2.1.1.2 Windows Versions 18 2.1.1.3 Windows GUI 19 2.1.1.4 Operating System Vulnerabilities 19 2.1.2 Windows Architecture and Operations 20 2.1.2.1 Hardware Abstraction Layer 20 2.1.2.2 User Mode and Kernel Mode 21 2.1.2.3 Windows File Systems 21 2.1.2.4 Windows Boot Process 23 2.1.2.5 Windows Startup and Shutdown 24 2.1.2.6 Processes, Threads, and Services 25 2.1.2.7 Memory Allocation and Handles 25 2.1.2.8 The Windows Registry 26 2.1.2.9 Activity - Identify the Windows Registry Hive 27 2.1.2.10 Lab - Exploring Processes, Threads, Handles, and Windows Registry 27 2.2 Windows Administration 27 2.2.1 Windows Configuration and Monitoring 27 2.2.1.1 Run as Administrator 27 2.2.1.2 Local Users and Domains 27 2.2.1.3 CLI and PowerShell 28 2.2.1.4 Windows Management Instrumentation 29 2.2.1.5 The net Command 30 2.2.1.6 Task Manager and Resource Monitor 30 2.2.1.7 Networking 31 2.2.1.8 Accessing Network Resources 33 2.2.1.9 Windows Server 33 2.2.1.10 Lab - Create User Accounts 34 2.2.1.11 Lab - Using Windows PowerShell 34 2.2.1.12 Lab - Windows Task Manager 34 2.2.1.13 Lab - Monitor and Manage System Resources in Windows 34 2.2.2 Windows Security 34 2.2.2.1 The netstat Command 34 2.2.2.2 Event Viewer 35 2.2.2.3 Windows Update Management 35 2.2.2.4 Local Security Policy 35 2.2.2.5 Windows Defender 36 2.2.2.6 Windows Firewall 37 2.2.2.7 Activity - Identify the Windows Command 37 2.2.2.8 Activity - Identify the Windows Tool 37 2.3 Summary 37 Chapter 3 Linux Operating System 41 3.0 Introduction 41 3.1 Linux Overview 41 3.1.1 Linux Basics 41 3.1.1.1 What is Linux? 41 3.1.1.2 The Value of Linux 42 3.1.1.3 Linux in the SOC 42 3.1.1.4 Linux Tools 43 3.1.2 Working in the Linux Shell 43 3.1.2.1 The Linux Shell 43 3.1.2.2 Basic Commands 43 3.1.2.3 File and Directory Commands 44 3.1.2.4 Working with Text Files 44 3.1.2.5 The Importance of Text Files in Linux 44 3.1.2.6 Lab - Working with Text Files in the CLI 45 3.1.2.7 Lab - Getting Familiar with the Linux Shell 45 3.1.3 Linux Servers and Clients 45 3.1.3.1 An Introduction to Client-Server Communications 45 3.1.3.2 Servers, Services, and Their Ports 45 3.1.3.3 Clients 45 3.1.3.4 Lab - Linux Servers 45 3.2 Linux Administration 46 3.2.1 Basic Server Administration 46 3.2.1.1 Service Configuration Files 46 3.2.1.2 Hardening Devices 46 3.2.1.3 Monitoring Service Logs 47 3.2.1.4 Lab - Locating Log Files 48 3.2.2 The Linux File System 48 3.2.2.1 The File System Types in Linux 48 3.2.2.2 Linux Roles and File Permissions 49 3.2.2.3 Hard Links and Symbolic Links 50 3.2.2.4 Lab - Navigating the Linux Filesystem and Permission Settings 50 3.3 Linux Hosts 51 3.3.1 Working with the Linux GUI 51 3.3.1.1 X Window System 51 3.3.1.2 The Linux GUI 51 3.3.2 Working on a Linux Host 52 3.3.2.1 Installing and Running Applications on a Linux Host 52 3.3.2.2 Keeping the System Up To Date 52 3.3.2.3 Processes and Forks 52 3.3.2.4 Malware on a Linux Host 53 3.3.2.5 Rootkit Check 54 3.3.2.6 Piping Commands 54 3.3.2.7 Video Demonstration - Applications, Rootkits, and Piping Commands 55 3.4 Summary 55 Chapter 4 Network Protocols and Services 59 4.0 Introduction 59 4.1 Network Protocols 59 4.1.1 Network Communications Process 59 4.1.1.1 Views of the Network 59 4.1.1.2 Client-Server Communications 60 4.1.1.3 A Typical Session: Student 60 4.1.1.4 A Typical Session: Gamer 61 4.1.1.5 A Typical Session: Surgeon 61 4.1.1.6 Tracing the Path 62 4.1.1.7 Lab - Tracing a Route 62 4.1.2 Communications Protocols 62 4.1.2.1 What are Protocols? 62 4.1.2.2 Network Protocol Suites 63 4.1.2.3 The TCP/IP Protocol Suite 63 4.1.2.4 Format, Size, and Timing 64 4.1.2.5 Unicast, Multicast, and Broadcast 64 4.1.2.6 Reference Models 65 4.1.2.7 Three Addresses 65 4.1.2.8 Encapsulation 65 4.1.2.9 Scenario: Sending and Receiving a Web Page 66 4.1.2.10 Lab - Introduction to Wireshark 67 4.2 Ethernet and Internet Protocol (IP) 67 4.2.1 Ethernet 67 4.2.1.1 The Ethernet Protocol 67 4.2.1.2 The Ethernet Frame 68 4.2.1.3 MAC Address Format 68 4.2.1.4 Activity - Ethernet Frame Fields 68 4.2.2 IPv4 68 4.2.2.1 IPv4 Encapsulation 68 4.2.2.2 IPv4 Characteristics 69 4.2.2.3 Activity - IPv4 Characteristics 70 4.2.2.4 The IPv4 Packet 70 4.2.2.5 Video Demonstration - Sample IPv4 Headers in Wireshark 70 4.2.3 IPv4 Addressing Basics 70 4.2.3.1 IPv4 Address Notation 70 4.2.3.2 IPv4 Host Address Structure 70 4.2.3.3 IPv4 Subnet Mask and Network Address 71 4.2.3.4 Subnetting Broadcast Domains 71 4.2.3.5 Video Demonstration - Network, Host, and Broadcast Addresses 72 4.2.4 Types of IPv4 Addresses 72 4.2.4.1 IPv4 Address Classes and Default Subnet Masks 72 4.2.4.2 Reserved Private Addresses 73 4.2.5 The Default Gateway 73 4.2.5.1 Host Forwarding Decision 73 4.2.5.2 Default Gateway 74 4.2.5.3 Using the Default Gateway 74 4.2.6 IPv6 75 4.2.6.1 Need for IPv6 75 4.2.6.2 IPv6 Size and Representation 75 4.2.6.3 IPv6 Address Formatting 75 4.2.6.4 IPv6 Prefix Length 76 4.2.6.5 Activity - IPv6 Address Notation 76 4.2.6.6 Video Tutorial - Layer 2 and Layer 3 Addressing 76 4.3 Connectivity Verification 76 4.3.1 ICMP 76 4.3.1.1 ICMPv4 Messages 76 4.3.1.2 ICMPv6 RS and RA Messages 77 4.3.2 Ping and Traceroute Utilities 78 4.3.2.1 Ping - Testing the Local Stack 78 4.3.2.2 Ping - Testing Connectivity to the Local LAN 79 4.3.2.3 Ping - Testing Connectivity to Remote Host 79 4.3.2.4 Traceroute - Testing the Path 80 4.3.2.5 ICMP Packet Format 80 4.4 Address Resolution Protocol 81 4.4.1 MAC and IP 81 4.4.1.1 Destination on Same Network 81 4.4.1.2 Destination on Remote Network 82 4.4.2 ARP 82 4.4.2.1 Introduction to ARP 82 4.4.2.2 ARP Functions 82 4.4.2.3 Video - ARP Operation - ARP Request 83 4.4.2.4 Video - ARP Operation - ARP Reply 84 4.4.2.5 Video - ARP Role in Remote Communication 84 4.4.2.6 Removing Entries from an ARP Table 85 4.4.2.7 ARP Tables on Networking Devices 85 4.4.2.8 Lab - Using Wireshark to Examine Ethernet Frames 85 4.4.3 ARP Issues 85 4.4.3.1 ARP Broadcasts 85 4.4.3.2 ARP Spoofing 86 4.5 The Transport Layer 86 4.5.1 Transport Layer Characteristics 86 4.5.1.1 Transport Layer Protocol Role in Network Communication 86 4.5.1.2 Transport Layer Mechanisms 87 4.5.1.3 TCP Local and Remote Ports 87 4.5.1.4 Socket Pairs 88 4.5.1.5 TCP vs UDP 88 4.5.1.6 TCP and UDP Headers 89 4.5.1.7 Activity - Compare TCP and UDP Characteristics 90 4.5.2 Transport Layer Operation 90 4.5.2.1 TCP Port Allocation 90 4.5.2.2 A TCP Session Part I: Connection Establishment and Termination 91 4.5.2.3 Video Demonstration - TCP 3-Way Handshake 92 4.5.2.4 Lab - Using Wireshark to Observe the TCP 3-Way Handshake 92 4.5.2.5 Activity - TCP Connection and Termination Process 92 4.5.2.6 A TCP Session Part II: Data Transfer 92 4.5.2.7 Video Demonstration - Sequence Numbers and Acknowledgments 94 4.5.2.8 Video Demonstration - Data Loss and Retransmission 94 4.5.2.9 A UDP Session 94 4.5.2.10 Lab - Exploring Nmap 95 4.6 Network Services 95 4.6.1 DHCP 95 4.6.1.1 DHCP Overview 95 4.6.1.2 DHCPv4 Message Format 96 4.6.2 DNS 97 4.6.2.1 DNS Overview 97 4.6.2.2 The DNS Domain Hierarchy 97 4.6.2.3 The DNS Lookup Process 97 4.6.2.4 DNS Message Format 98 4.6.2.5 Dynamic DNS 99 4.6.2.6 The WHOIS Protocol 99 4.6.2.7 Lab - Using Wireshark to Examine a UDP DNS Capture 100 4.6.3 NAT 100 4.6.3.1 NAT Overview 100 4.6.3.2 NAT-Enabled Routers 100 4.6.3.3 Port Address Translation 100 4.6.4 File Transfer and Sharing Services 101 4.6.4.1 FTP and TFTP 101 4.6.4.2 SMB 102 4.6.4.3 Lab - Using Wireshark to Examine TCP and UDP Captures 102 4.6.5 Email 102 4.6.5.1 Email Overview 102 4.6.5.2 SMTP 102 4.6.5.3 POP3 103 4.6.5.4 IMAP 103 4.6.6 HTTP 103 4.6.6.1 HTTP Overview 103 4.6.6.2 The HTTP URL 104 4.6.6.3 The HTTP Protocol 104 4.6.6.4 HTTP Status Codes 105 4.6.6.5 Lab - Using Wireshark to Examine HTTP and HTTPS Traffic 105 4.7 Summary 105 Chapter 5 Network Infrastructure 109 5.0 Introduction 109 5.1 Network Communication Devices 109 5.1.1 Network Devices 109 5.1.1.1 End Devices 109 5.1.1.2 Video Tutorial - End Devices 109 5.1.1.3 Routers 110 5.1.1.4 Activity - Match Layer 2 and Layer 3 Addressing 110 5.1.1.5 Router Operation 110 5.1.1.6 Routing Information 111 5.1.1.7 Video Tutorial - Static and Dynamic Routing 112 5.1.1.8 Hubs, Bridges, LAN Switches 112 5.1.1.9 Switching Operation 113 5.1.1.10 Video Tutorial - MAC Address Tables on Connected Switches 114 5.1.1.11 VLANs 114 5.1.1.12 STP 114 5.1.1.13 Multilayer Switching 115 5.1.2 Wireless Communications 116 5.1.2.1 Video Tutorial - Wireless Communications 116 5.1.2.2 Protocols and Features 116 5.1.2.3 Wireless Network Operations 117 5.1.2.4 The Client to AP Association Process 118 5.1.2.5 Activity - Order the Steps in the Client and AP Association Process 119 5.1.2.6 Wireless Devices - AP, LWAP, WLC 119 5.1.2.7 Activity - Identify the LAN Device 119 5.2 Network Security Infrastructure 120 5.2.1 Security Devices 120 5.2.1.1 Video Tutorial - Security Devices 120 5.2.1.2 Firewalls 120 5.2.1.3 Firewall Type Descriptions 120 5.2.1.4 Packet Filtering Firewalls 121 5.2.1.5 Stateful Firewalls 121 5.2.1.6 Next-Generation Firewalls 121 5.2.1.7 Activity - Identify the Type of Firewall 122 5.2.1.8 Intrusion Protection and Detection Devices 122 5.2.1.9 Advantages and Disadvantages of IDS and IPS 122 5.2.1.10 Types of IPS 123 5.2.1.11 Specialized Security Appliances 124 5.2.1.12 Activity - Compare IDS and IPS Characteristics 125 5.2.2 Security Services 125 5.2.2.1 Video Tutorial - Security Services 125 5.2.2.2 Traffic Control with ACLs 125 5.2.2.3 ACLs: Important Features 126 5.2.2.4 Packet Tracer - ACL Demonstration 126 5.2.2.5 SNMP 126 5.2.2.6 NetFlow 127 5.2.2.7 Port Mirroring 127 5.2.2.8 Syslog Servers 128 5.2.2.9 NTP 128 5.2.2.10 AAA Servers 129 5.2.2.11 VPN 130 5.2.2.12 Activity - Identify the Network Security Device or Service 130 5.3 Network Representations 130 5.3.1 Network Topologies 130 5.3.1.1 Overview of Network Components 130 5.3.1.2 Physical and Logical Topologies 131 5.3.1.3 WAN Topologies 131 5.3.1.4 LAN Topologies 131 5.3.1.5 The Three-Layer Network Design Model 132 5.3.1.6 Video Tutorial - Three-Layer Network Design 132 5.3.1.7 Common Security Architectures 133 5.3.1.8 Activity - Identify the Network Topology 134 5.3.1.9 Activity - Identify the Network Design Terminology 134 5.3.1.10 Packet Tracer - Identify Packet Flow 134 5.4 Summary 134 Chapter 6 Principles of Network Security 137 6.0 Introduction 137 6.1 Attackers and Their Tools 137 6.1.1 Who is Attacking Our Network? 137 6.1.1.1 Threat, Vulnerability, and Risk 137 6.1.1.2 Hacker vs. Threat Actor 138 6.1.1.3 Evolution of Threat Actors 138 6.1.1.4 Cybercriminals 139 6.1.1.5 Cybersecurity Tasks 139 6.1.1.6 Cyber Threat Indicators 139 6.1.1.7 Activity - What Color is my Hat? 140 6.1.2 Threat Actor Tools 140 6.1.2.1 Introduction of Attack Tools 140 6.1.2.2 Evolution of Security Tools 140 6.1.2.3 Categories of Attacks 141 6.1.2.4 Activity - Classify Hacking Tools 141 6.2 Common Threats and Attacks 141 6.2.1 Malware 141 6.2.1.1 Types of Malware 141 6.2.1.2 Viruses 141 6.2.1.3 Trojan Horses 141 6.2.1.4 Trojan Horse Classification 142 6.2.1.5 Worms 142 6.2.1.6 Worm Components 143 6.2.1.7 Ransomware 143 6.2.1.8 Other Malware 144 6.2.1.9 Common Malware Behaviors 144 6.2.1.10 Activity - Identify the Malware Type 145 6.2.1.11 Lab - Anatomy of Malware 145 6.2.2 Common Network Attacks 145 6.2.2.1 Types of Network Attacks 145 6.2.2.2 Reconnaissance Attacks 145 6.2.2.3 Sample Reconnaissance Attacks 146 6.2.2.4 Access Attacks 146 6.2.2.5 Types of Access Attacks 147 6.2.2.6 Social Engineering Attacks 147 6.2.2.7 Phishing Social Engineering Attacks 148 6.2.2.8 Strengthening the Weakest Link 149 6.2.2.9 Lab - Social Engineering 149 6.2.2.10 Denial of Service Attacks 149 6.2.2.11 DDoS Attacks 149 6.2.2.12 Example DDoS Attack 150 6.2.2.13 Buffer Overflow Attack 150 6.2.2.14 Evasion Methods 151 6.2.2.15 Activity - Identify the Types of Network Attack 151 6.2.2.16 Activity - Components of a DDoS Attack 151 6.3 Summary 152 Chapter 7 Network Attacks: A Deeper Look 155 7.0 Introduction 155 7.1 Attackers and Their Tools 155 7.1.1 Who is Attacking Our Network? 155 7.1.1.1 Network Security Topology 155 7.1.1.2 Monitoring the Network 156 7.1.1.3 Network Taps 156 7.1.1.4 Traffic Mirroring and SPAN 156 7.1.2 Introduction to Network Monitoring Tools 157 7.1.2.1 Network Security Monitoring Tools 157 7.1.2.2 Network Protocol Analyzers 157 7.1.2.3 NetFlow 158 7.1.2.4 SIEM 159 7.1.2.5 SIEM Systems 159 7.1.2.6 Activity - Identify the Network Monitoring Tool 159 7.1.2.7 Packet Tracer - Logging Network Activity 159 7.2 Attacking the Foundation 160 7.2.1 IP Vulnerabilities and Threats 160 7.2.1.1 IPv4 and IPv6 160 7.2.1.2 The IPv4 Packet Header 160 7.2.1.3 The IPv6 Packet Header 161 7.2.1.4 IP Vulnerabilities 161 7.2.1.5 ICMP Attacks 162 7.2.1.6 DoS Attacks 163 7.2.1.7 Amplification and Reflection Attacks 163 7.2.1.8 DDoS Attacks 163 7.2.1.9 Address Spoofing Attacks 164 7.2.1.10 Activity - Identify the IP Vulnerability 164 7.2.1.11 Lab - Observing a DDoS Attack 164 7.2.2 TCP and UDP Vulnerabilities 165 7.2.2.1 TCP 165 7.2.2.2 TCP Attacks 165 7.2.2.3 UDP and UDP Attacks 166 7.2.2.4 Lab - Observing TCP Anomalies 166 7.3 Attacking What We Do 167 7.3.1 IP Services 167 7.3.1.1 ARP Vulnerabilities 167 7.3.1.2 ARP Cache Poisoning 167 7.3.1.3 DNS Attacks 168 7.3.1.4 DNS Tunneling 169 7.3.1.5 DHCP 169 7.3.1.6 Lab - Exploring DNS Traffic 170 7.3.2 Enterprise Services 170 7.3.2.1 HTTP and HTTPS 170 7.3.2.2 Email 173 7.3.2.3 Web-Exposed Databases 174 7.3.2.4 Lab - Attacking a MySQL Database 176 7.3.2.5 Lab - Reading Server Logs 176 7.3.2.6 Lab - Reading Server Logs 176 7.4 Summary 176 Chapter 8 Protecting the Network 179 8.0 Introduction 179 8.1 Understanding Defense 179 8.1.1 Defense-in-Depth 179 8.1.1.1 Assets, Vulnerabilities, Threats 179 8.1.1.2 Identify Assets 179 8.1.1.3 Identify Vulnerabilities 180 8.1.1.4 Identify Threats 181 8.1.1.5 Security Onion and Security Artichoke Approaches 181 8.1.2 Security Policies 182 8.1.2.1 Business Policies 182 8.1.2.2 Security Policy 182 8.1.2.3 BYOD Policies 183 8.1.2.4 Regulatory and Standard Compliance 184 8.2 Access Control 184 8.2.1 Access Control Concepts 184 8.2.1.1 Communications Security: CIA 184 8.2.1.2 Access Control Models 185 8.2.1.3 Activity - Identify the Access Control Model 185 8.2.2 AAA Usage and Operation 185 8.2.2.1 AAA Operation 185 8.2.2.2 AAA Authentication 186 8.2.2.3 AAA Accounting Logs 187 8.2.2.4 Activity - Identify the Characteristic of AAA 187 8.3 Threat Intelligence 187 8.3.1 Information Sources 187 8.3.1.1 Network Intelligence Communities 187 8.3.1.2 Cisco Cybersecurity Reports 188 8.3.1.3 Security Blogs and Podcasts 188 8.3.2 Threat Intelligence Services 188 8.3.2.1 Cisco Talos 188 8.3.2.2 FireEye 189 8.3.2.3 Automated Indicator Sharing 189 8.3.2.4 Common Vulnerabilities and Exposures Database 189 8.3.2.5 Threat Intelligence Communication Standards 189 8.3.2.6 Activity - Identify the Threat Intelligence Information Source 190 8.4 Summary 190 Chapter 9 Cryptography and the Public Key Infrastructure 193 9.0 Introduction 193 9.1 Cryptography 193 9.1.1 What is Cryptography? 193 9.1.1.1 Securing Communications 193 9.1.1.2 Cryptology 194 9.1.1.3 Cryptography - Ciphers 195 9.1.1.4 Cryptanalysis - Code Breaking 195 9.1.1.5 Keys 196 9.1.1.6 Lab - Encrypting and Decrypting Data Using OpenSSL 197 9.1.1.7 Lab - Encrypting and Decrypting Data Using a Hacker Tool 197 9.1.1.8 Lab - Examining Telnet and SSH in Wireshark 197 9.1.2 Integrity and Authenticity 197 9.1.2.1 Cryptographic Hash Functions 197 9.1.2.2 Cryptographic Hash Operation 198 9.1.2.3 MD5 and SHA 198 9.1.2.4 Hash Message Authentication Code 199 9.1.2.5 Lab - Hashing Things Out 200 9.1.3 Confidentiality 200 9.1.3.1 Encryption 200 9.1.3.2 Symmetric Encryption 200 9.1.3.3 Symmetric Encryption Algorithms 201 9.1.3.4 Asymmetric Encryption Algorithms 202 9.1.3.5 Asymmetric Encryption - Confidentiality 202 9.1.3.6 Asymmetric Encryption - Authentication 203 9.1.3.7 Asymmetric Encryption - Integrity 203 9.1.3.8 Diffie-Hellman 204 9.1.3.9 Activity - Classify the Encryption Algorithms 204 9.2 Public Key Infrastructure 204 9.2.1 Public Key Cryptography 204 9.2.1.1 Using Digital Signatures 204 9.2.1.2 Digital Signatures for Code Signing 206 9.2.1.3 Digital Signatures for Digital Certificates 206 9.2.1.4 Lab - Create a Linux Playground 206 9.2.2 Authorities and the PKI Trust System 206 9.2.2.1 Public Key Management 206 9.2.2.2 The Public Key Infrastructure 207 9.2.2.3 The PKI Authorities System 207 9.2.2.4 The PKI Trust System 208 9.2.2.5 Interoperability of Different PKI Vendors 208 9.2.2.6 Certificate Enrollment, Authentication, and Revocation 209 9.2.2.7 Lab - Certificate Authority Stores 209 9.2.3 Applications and Impacts of Cryptography 210 9.2.3.1 PKI Applications 210 9.2.3.2 Encrypting Network Transactions 210 9.2.3.3 Encryption and Security Monitoring 211 9.3 Summary 212 Chapter 10 Endpoint Security and Analysis 215 10.0 Introduction 215 10.1 Endpoint Protection 215 10.1.1 Antimalware Protection 215 10.1.1.1 Endpoint Threats 215 10.1.1.2 Endpoint Security 216 10.1.1.3 Host-Based Malware Protection 216 10.1.1.4 Network-Based Malware Protection 217 10.1.1.5 Cisco Advanced Malware Protection (AMP) 218 10.1.1.6 Activity - Identify Antimalware Terms and Concepts 218 10.1.2 Host-Based Intrusion Protection 218 10.1.2.1 Host-Based Firewalls 218 10.1.2.2 Host-Based Intrusion Detection 219 10.1.2.3 HIDS Operation 220 10.1.2.4 HIDS Products 220 10.1.2.5 Activity - Identify the Host-Based Intrusion Protection Terminology 220 10.1.3 Application Security 221 10.1.3.1 Attack Surface 221 10.1.3.2 Application Blacklisting and Whitelisting 221 10.1.3.3 System-Based Sandboxing 222 10.1.3.4 Video Demonstration - Using a Sandbox to Launch Malware 222 10.2 Endpoint Vulnerability Assessment 222 10.2.1 Network and Server Profiling 222 10.2.1.1 Network Profiling 222 10.2.1.2 Server Profiling 223 10.2.1.3 Network Anomaly Detection 223 10.2.1.4 Network Vulnerability Testing 224 10.2.1.5 Activity - Identify the Elements of Network Profiling 225 10.2.2 Common Vulnerability Scoring System (CVSS) 225 10.2.2.1 CVSS Overview 225 10.2.2.2 CVSS Metric Groups 225 10.2.2.3 CVSS Base Metric Group 226 10.2.2.4 The CVSS Process 226 10.2.2.5 CVSS Reports 227 10.2.2.6 Other Vulnerability Information Sources 227 10.2.2.7 Activity - Identify CVSS Metrics 228 10.2.3 Compliance Frameworks 228 10.2.3.1 Compliance Regulations 228 10.2.3.2 Overview of Regulatory Standards 228 10.2.3.3 Activity - Identify Regulatory Standards 229 10.2.4 Secure Device Management 230 10.2.4.1 Risk Management 230 10.2.4.2 Activity - Identify the Risk Response 231 10.2.4.3 Vulnerability Management 231 10.2.4.4 Asset Management 231 10.2.4.5 Mobile Device Management 232 10.2.4.6 Configuration Management 232 10.2.4.7 Enterprise Patch Management 233 10.2.4.8 Patch Management Techniques 233 10.2.4.9 Activity - Identify Device Management Activities 234 10.2.5 Information Security Management Systems 234 10.2.5.1 Security Management Systems 234 10.2.5.2 ISO-27001 234 10.2.5.3 NIST Cybersecurity Framework 234 10.2.5.4 Activity - Identify the ISO 27001 Activity Cycle 235 10.2.5.5 Activity - Identify the Stages in the NIST Cybersecurity Framework 235 10.3 Summary 235 Chapter 11 Security Monitoring 239 11.0 Introduction 239 11.1 Technologies and Protocols 239 11.1.1 Monitoring Common Protocols 239 11.1.1.1 Syslog and NTP 239 11.1.1.2 NTP 240 11.1.1.3 DNS 240 11.1.1.4 HTTP and HTTPS 241 11.1.1.5 Email Protocols 241 11.1.1.6 ICMP 242 11.1.1.7 Activity - Identify the Monitored Protocol 242 11.1.2 Security Technologies 242 11.1.2.1 ACLs 242 11.1.2.2 NAT and PAT 242 11.1.2.3 Encryption, Encapsulation, and Tunneling 243 11.1.2.4 Peer-to-Peer Networking and Tor 243 11.1.2.5 Load Balancing 244 11.1.2.6 Activity - Identify the Impact of the Technology on Security and Monitoring 244 11.2 Log Files 244 11.2.1 Types of Security Data 244 11.2.1.1 Alert Data 244 11.2.1.2 Session and Transaction Data 245 11.2.1.3 Full Packet Captures 245 11.2.1.4 Statistical Data 246 11.2.1.5 Activity - Identify Types of Network Monitoring Data 246 11.2.2 End Device Logs 246 11.2.2.1 Host Logs 246 11.2.2.2 Syslog 247 11.2.2.3 Server Logs 248 11.2.2.4 Apache Webserver Access Logs 248 11.2.2.5 IIS Access Logs 249 11.2.2.6 SIEM and Log Collection 249 11.2.2.7 Activity - Identify Information in Logged Events 250 11.2.3 Network Logs 250 11.2.3.1 Tcpdump 250 11.2.3.2 NetFlow 250 11.2.3.3 Application Visibility and Control 251 11.2.3.4 Content Filter Logs 251 11.2.3.5 Logging from Cisco Devices 252 11.2.3.6 Proxy Logs 252 11.2.3.7 NextGen IPS 253 11.2.3.8 Activity - Identify the Security Technology from the Data Description 254 11.2.3.9 Activity - Identify the NextGen IPS Event Type 254 11.2.3.10 Packet Tracer - Explore a NetFlow Implementation 254 11.2.3.11 Packet Tracer - Logging from Multiple Sources 254 11.3 Summary 254 Chapter 12 Intrusion Data Analysis 257 12.0 Introduction 257 12.1 Evaluating Alerts 257 12.1.1 Sources of Alerts 257 12.1.1.1 Security Onion 257 12.1.1.2 Detection Tools for Collecting Alert Data 257 12.1.1.3 Analysis Tools 258 12.1.1.4 Alert Generation 259 12.1.1.5 Rules and Alerts 260 12.1.1.6 Snort Rule Structure 260 12.1.1.7 Lab - Snort and Firewall Rules 261 12.1.2 Overview of Alert Evaluation 262 12.1.2.1 The Need for Alert Evaluation 262 12.1.2.2 Evaluating Alerts 262 12.1.2.3 Deterministic Analysis and Probabilistic Analysis 263 12.1.2.4 Activity - Identify Deterministic and Probabilistic Scenarios 264 12.1.2.5 Activity - Identify the Alert Classification 264 12.2 Working with Network Security Data 264 12.2.1 A Common Data Platform 264 12.2.1.1 ELSA 264 12.2.1.2 Data Reduction 264 12.2.1.3 Data Normalization 265 12.2.1.4 Data Archiving 265 12.2.1.5 Lab - Convert Data into a Universal Format 266 12.2.1.6 Investigating Process or API Calls 266 12.2.2 Investigating Network Data 266 12.2.2.1 Working in Sguil 266 12.2.2.2 Sguil Queries 267 12.2.2.3 Pivoting from Sguil 267 12.2.2.4 Event Handling in Sguil 268 12.2.2.5 Working in ELSA 268 12.2.2.6 Queries in ELSA 269 12.2.2.7 Investigating Process or API Calls 269 12.2.2.8 Investigating File Details 270 12.2.2.9 Lab - Regular Expression Tutorial 270 12.2.2.10 Lab - Extract an Executable from a PCAP 270 12.2.3 Enhancing the Work of the Cybersecurity Analyst 270 12.2.3.1 Dashboards and Visualizations 270 12.2.3.2 Workflow Management 271 12.3 Digital Forensics 271 12.3.1 Evidence Handling and Attack Attribution 271 12.3.1.1 Digital Forensics 271 12.3.1.2 The Digital Forensics Process 272 12.3.1.3 Types of Evidence 272 12.3.1.4 Evidence Collection Order 273 12.3.1.5 Chain of Custody 273 12.3.1.6 Data Integrity and Preservation 274 12.3.1.7 Attack Attribution 274 12.3.1.8 Activity - Identify the Type of Evidence 275 12.3.1.9 Activity - Identify the Forensic Technique Terminology 275 12.4 Summary 275 Chapter 13 Incident Response and Handling 277 13.0 Introduction 277 13.1 Incident Response Models 277 13.1.1 The Cyber Kill Chain 277 13.1.1.1 Steps of the Cyber Kill Chain 277 13.1.1.2 Reconnaissance 278 13.1.1.3 Weaponization 278 13.1.1.4 Delivery 278 13.1.1.5 Exploitation 279 13.1.1.6 Installation 279 13.1.1.7 Command and Control 279 13.1.1.8 Actions on Objectives 279 13.1.1.9 Activity - Identify the Kill Chain Step 279 13.1.2 The Diamond Model of Intrusion 280 13.1.2.1 Diamond Model Overview 280 13.1.2.2 Pivoting Across the Diamond Model 280 13.1.2.3 The Diamond Model and the Cyber Kill Chain 281 13.1.2.4 Activity - Identify the Diamond Model Features 282 13.1.3 The VERIS Schema 282 13.1.3.1 What is the VERIS Schema? 282 13.1.3.2 Create a VERIS Record 282 13.1.3.3 Top-Level and Second-Level Elements 283 13.1.3.4 The VERIS Community Database 285 13.1.3.5 Activity - Apply the VERIS Schema to an Incident 285 13.2 Incident Handling 285 13.2.1 CSIRTs 285 13.2.1.1 CSIRT Overview 285 13.2.1.2 Types of CSIRTs 286 13.2.1.3 CERT 286 13.2.1.4 Activity - Match the CSIRT with the CSIRT Goal 287 13.2.2 NIST 800-61r2 287 13.2.2.1 Establishing an Incident Response Capability 287 13.2.2.2 Incident Response Stakeholders 288 13.2.2.3 NIST Incident Response Life Cycle 288 13.2.2.4 Preparation 289 13.2.2.5 Detection and Analysis 290 13.2.2.6 Containment, Eradication, and Recovery 291 13.2.2.7 Post-Incident Activities 293 13.2.2.8 Incident Data Collection and Retention 294 13.2.2.9 Reporting Requirements and Information Sharing 295 13.2.2.10 Activity - Identify the Incident Response Plan Elements 296 13.2.2.11 Activity - Identify the Incident Handling Term 296 13.2.2.12 Activity - Identify the Incident Handling Step 296 13.2.2.13 Lab - Incident Handling 296 13.3 Summary 296 9781587134371 TOC 3/7/2018
£29.10
Pearson Education (US) Data Analytics for IT Networks: Developing
Book SynopsisUse data analytics to drive innovation and value throughout your network infrastructure Network and IT professionals capture immense amounts of data from their networks. Buried in this data are multiple opportunities to solve and avoid problems, strengthen security, and improve network performance. To achieve these goals, IT networking experts need a solid understanding of data science, and data scientists need a firm grasp of modern networking concepts. Data Analytics for IT Networks fills these knowledge gaps, allowing both groups to drive unprecedented value from telemetry, event analytics, network infrastructure metadata, and other network data sources. Drawing on his pioneering experience applying data science to large-scale Cisco networks, John Garrett introduces the specific data science methodologies and algorithms network and IT professionals need, and helps data scientists understand contemporary network technologies, applications, and data sources. After establishing this shared understanding, Garrett shows how to uncover innovative use cases that integrate data science algorithms with network data. He concludes with several hands-on, Python-based case studies reflecting Cisco Customer Experience (CX) engineers’ supporting its largest customers. These are designed to serve as templates for developing custom solutions ranging from advanced troubleshooting to service assurance. Understand the data analytics landscape and its opportunities in Networking See how elements of an analytics solution come together in the practical use cases Explore and access network data sources, and choose the right data for your problem Innovate more successfully by understanding mental models and cognitive biases Walk through common analytics use cases from many industries, and adapt them to your environment Uncover new data science use cases for optimizing large networks Master proven algorithms, models, and methodologies for solving network problems Adapt use cases built with traditional statistical methods Use data science to improve network infrastructure analysisAnalyze control and data planes with greater sophistication Fully leverage your existing Cisco tools to collect, analyze, and visualize data Table of Contents Foreword xvii Introduction: Your future is in your hands! xviiiChapter 1 Getting Started with Analytics 1 What This Chapter Covers 1 Data: You as the SME 2 Use-Case Development with Bias and Mental Models 2 Data Science: Algorithms and Their Purposes 3 What This Book Does Not Cover 4 Building a Big Data Architecture 4 Microservices Architectures and Open Source Software 5 R Versus Python Versus SAS Versus Stata 6 Databases and Data Storage 6 Cisco Products in Detail 6 Analytics and Literary Perspectives 7 Analytics Maturity 7 Knowledge Management 8 Gartner Analytics 8 Strategic Thinking 9 Striving for “Up and to the Right” 9 Moving Your Perspective 10 Hot Topics in the Literature 11 Summary 12Chapter 2 Approaches for Analytics and Data Science 13 Model Building and Model Deployment 14 Analytics Methodology and Approach 15 Common Approach Walkthrough 16 Distinction Between the Use Case and the Solution 18 Logical Models for Data Science and Data 19 Analytics as an Overlay 20 Analytics Infrastructure Model 22 Summary 33Chapter 3 Understanding Networking Data Sources 35 Planes of Operation on IT Networks 36 Review of the Planes 40 Data and the Planes of Operation 42 Planes Data Examples 44 A Wider Rabbit Hole 49 A Deeper Rabbit Hole 51 Summary 53Chapter 4 Accessing Data from Network Components 55 Methods of Networking Data Access 55 Pull Data Availability 57 Push Data Availability 61 Control Plane Data 67 Data Plane Traffic Capture 68 Packet Data 70 Other Data Access Methods 74 Data Types and Measurement Considerations 76 Numbers and Text 77 Data Structure 82 Data Manipulation 84 Other Data Considerations 87 External Data for Context 89 Data Transport Methods 89 Transport Considerations for Network Data Sources 90 Summary 96Chapter 5 Mental Models and Cognitive Bias 97 Changing How You Think 98 Domain Expertise, Mental Models, and Intuition 99 Mental Models 99 Daniel Kahneman’s System 1 and System 2 102 Intuition 103 Opening Your Mind to Cognitive Bias 104 Changing Perspective, Using Bias for Good 105 Your Bias and Your Solutions 106 How You Think: Anchoring, Focalism, Narrative Fallacy, Framing, and Priming 107 How Others Think: Mirroring 110 What Just Happened? Availability, Recency, Correlation, Clustering, and Illusion of Truth 111 Enter the Boss: HIPPO and Authority Bias 113 What You Know: Confirmation, Expectation, Ambiguity, Context, and Frequency Illusion 114 What You Don’t Know: Base Rates, Small Numbers, Group Attribution, and Survivorship 117 Your Skills and Expertise: Curse of Knowledge, Group Bias, and Dunning-Kruger 119 We Don’t Need a New System: IKEA, Not Invented Here, Pro-Innovation, Endowment, Status Quo, Sunk Cost, Zero Price, and Empathy 121 I Knew It Would Happen: Hindsight, Halo Effect, and Outcome Bias 123 Summary 124Chapter 6 Innovative Thinking Techniques 127 Acting Like an Innovator and Mindfulness 128 Innovation Tips and Techniques 129 Developing Analytics for Your Company 140 Defocusing, Breaking Anchors, and Unpriming 140 Lean Thinking 142 Cognitive Trickery 143 Quick Innovation Wins 143 Summary 144Chapter 7 Analytics Use Cases and the Intuition Behind Them 147 Analytics Definitions 150 How to Use the Information from This Chapter 151 Priming and Framing Effects 151 Analytics Rube Goldberg Machines 151 Popular Analytics Use Cases 152 Machine Learning and Statistics Use Cases 153 Common IT Analytics Use Cases 170 Broadly Applicable Use Cases 199 Some Final Notes on Use Cases 214 Summary 214Chapter 8 Analytics Algorithms and the Intuition Behind Them 217 About the Algorithms 217 Algorithms and Assumptions 218 Additional Background 219 Data and Statistics 221 Statistics 221 Correlation 224 Longitudinal Data 225 ANOVA 227 Probability 228 Bayes’ Theorem 228 Feature Selection 230 Data-Encoding Methods 232 Dimensionality Reduction 233 Unsupervised Learning 234 Clustering 234 Association Rules 240 Sequential Pattern Mining 243 Collaborative Filtering 244 Supervised Learning 246 Regression Analysis 246 Classification Algorithms 248 Decision Trees 249 Random Forest 250 Gradient Boosting Methods 251 Neural Networks 252 Support Vector Machines 258 Time Series Analysis 259 Text and Document Analysis 262 Natural Language Processing (NLP) 262 Information Retrieval 263 Topic Modeling 265 Sentiment Analysis 266 Other Analytics Concepts 267 Artificial Intelligence 267 Confusion Matrix and Contingency Tables 267 Cumulative Gains and Lift 269 Simulation 271 Summary 271Chapter 9 Building Analytics Use Cases 273 Designing Your Analytics Solutions 274 Using the Analytics Infrastructure Model 275 About the Upcoming Use Cases 276 The Data 276 The Data Science 278 The Code 280 Operationalizing Solutions as Use Cases 281 Understanding and Designing Workflows 282 Tips for Setting Up an Environment to Do Your Own Analysis 282 Summary 284Chapter 10 Developing Real Use Cases: The Power of Statistics 285 Loading and Exploring Data 286 Base Rate Statistics for Platform Crashes 288 Base Rate Statistics for Software Crashes 299 ANOVA 305 Data Transformation 310 Tests for Normality 311 Examining Variance 313 Statistical Anomaly Detection 318 Summary 321Chapter 11 Developing Real Use Cases: Network Infrastructure Analytics 323 Human DNA and Fingerprinting 324 Building Search Capability 325 Loading Data and Setting Up the Environment 325 Encoding Data for Algorithmic Use 328 Search Challenges and Solutions 331 Other Uses of Encoded Data 336 Dimensionality Reduction 337 Data Visualization 340 K-Means Clustering 344 Machine Learning Guided Troubleshooting 350 Summary 353Chapter 12 Developing Real Use Cases: Control Plane Analytics Using Syslog Telemetry 355 Data for This Chapter 356 OSPF Routing Protocols 357 Non-Machine Learning Log Analysis Using pandas 357 Noise Reduction 360 Finding the Hotspots 362 Machine Learning—Based Log Evaluation 366 Data Visualization 367 Cleaning and Encoding Data 369 Clustering 373 More Data Visualization 375 Transaction Analysis 379 Task List 386 Summary 387Chapter 13 Developing Real Use Cases: Data Plane Analytics 389 The Data 390 SME Analysis 394 SME Port Clustering 407 Machine Learning: Creating Full Port Profiles 413 Machine Learning: Creating Source Port Profiles 419 Asset Discovery 422 Investigation Task List 423 Summary 424Chapter 14 Cisco Analytics 425 Architecture and Advisory Services for Analytics 426 Stealthwatch 427 Digital Network Architecture (DNA) 428 AppDynamics 428 Tetration 430 Crosswork Automation 431 IoT Analytics 432 Analytics Platforms and Partnerships 433 Cisco Open Source Platform 433 Summary 434Chapter 15 Book Summary 435 Analytics Introduction and Methodology 436 All About Networking Data 438 Using Bias and Innovation to Discover Solutions 439 Analytics Use Cases and Algorithms 439 Building Real Analytics Use Cases 440 Cisco Services and Solutions 442 In Closing 442Appendix A Function for Parsing Packets from pcap Files 4439781587145131, TOC, 9/19/18
£40.49
Nova Science Publishers Inc Technology Supporting Business Solutions
Book Synopsis
£67.99
APress Mastering Oracle PL/SQL: Practical Solutions
Book SynopsisIf you have mastered the fundamentals of the PL/SQL language and are now looking for an in-depth, practical guide to solving real problems with PL/SQL stored procedures, then this is the book for you. Table of Contents Efficient PL/SQL Package It All Up The Vexed Subject of Cursors Effective Data Handling PL/SQL Optimization Techniques Triggers DBA Packages Security Packages Web Packages PL/SQL Debugging
£37.52
APress Expert Oracle Database 10g Administration
Book Synopsis*One-stop reference for administration and management of Oracle 10g Database *9i predecessor was a best seller; this edition covers all new features, with fully field-tested examples—not just "showcase" examples *Contains essential primers on Unix, Linux and Windows NT management and on SQL and PL/SQL programming; ideal for new/aspiring DBAsTable of ContentsA table of contents is not available for this title.
£49.99
APress SQL Server 2005 T-SQL Recipes: A Problem-Solution
Book Synopsis* Comprehensive T-SQL Coverage, including all SQL Server 2005 new features, from an established SQL Server expert and author. * Broad appeal, with practical ‘How to’ answers to common SQL Server T-SQL questions for both novice and advanced DBAs and developers. * Unique, easy-reference format – ideal for preparing for a SQL Server job interview, or for a SQL Server certification testTable of ContentsA table of contents is not available for this title.
£37.49
APress Pro Oracle Application Express
Book SynopsisPro Oracle Application Express opens the "hood" of APEX and reveals the full power behind its easy-to-use GUI interface. This book shows you what you need to know to produce powerful, professionally polished applications: such as user-authentication models, approaches to layout and navigation, how to integrate Ajax, how to deal with localization issues like time zones and translations, how to customize the look and feel of an APEX web site, and more. The authors are well-qualified to write on APEX. John Scott is a hard-core APEX developer and his coauthor, Scott Spendolini, is one of the original creators of APEX.Table of ContentsA table of contents is not available for this title.
£41.32
Nova Science Publishers Inc Data Management in the Semantic Web
Book Synopsis
£155.99
Manning Publications Event Streams in Action: Real-time event systems
Book SynopsisDESCRIPTIONEvent Streams in Action is a foundational book introducing the ULPparadigm and presenting techniques to use it effectively in data-richenvironments. The book begins with an architectural overview,illustrating how ULP addresses the thorny issues associated withprocessing data from multiple sources. It then guides the readerthrough examples using the unified log technologies Apache Kafkaand Amazon Kinesis and a variety of stream processing frameworksand analytics databases. Readers learn to aggregate events frommultiple sources, store them in a unified log, and build data processingapplications on the resulting event streams. As readers progressthrough the book, they learn how to validate, filter, enrich, and storeevent streams, master key stream processing approaches, and exploreimportant patterns like the lambda architecture, stream aggregation,and event re-processing. The book also dives into the methods andtools usable for event modelling and event analytics, along withscaling, resiliency, and advanced stream patterns. KEY FEATURES • Building data-driven applications that are easier to design,deploy, and maintain• Uses real-world examples and techniques• Full of figures and diagrams• Hands-on code samples and walkthroughs This book assumes that the reader has written some Java code. SomeScala or Python experience is helpful but not required. ABOUT THE TECHNOLOGYUnified Log Processing is a coherent data processing architecture thatcombines batch and near-real time stream data, event logging andaggregation, and data processing into a unified event stream. By efficientlycreating a single log of events from multiple data sources, Unified LogProcessing makes it possible to design large-scale data-driven applicationsthat are easier to design, deploy, and maintain. AUTHOR BIOAlexander Dean is co-founder and technical lead of Snowplow Analytics,an open source event processing and analytics platform.
£32.39
Manning Publications Spark in Action
Book SynopsisWorking with big data can be complex and challenging, in part because of the multiple analysis frameworks and tools required. Apache Spark is a big data processing framework perfect for analyzing near-real-time streams and discovering historical patterns in batched data sets. But Spark goes much further than other frameworks. By including machine learning and graph processing capabilities, it makes many specialized data processing platforms obsolete. Spark's unified framework and programming model significantly lowers the initial infrastructure investment, and Spark's core abstractions are intuitive for most Scala, Java, and Python developers. Spark in Action teaches readers to use Spark for stream and batch data processing. It starts with an introduction to the Spark architecture and ecosystem followed by a taste of Spark's command line interface. Readers then discover the most fundamental concepts and abstractions of Spark, particularly Resilient Distributed Datasets (RDDs) and the basic data transformations that RDDs provide. The first part of the book covers writing Spark applications using the the core APIs. Readers also learn how to work with structured data using Spark SQL, how to process near-real time data with Spark Streaming, how to apply machine learning algorithms with Spark MLlib, how to apply graph algorithms on graph-shaped data using Spark GraphX, and an introduction to Spark clustering. Key Features: • Clear introduction to Spark • Teaches how to ingest near real-time data • Gaining value from big data • Includes real-life case studies AUDIENCE Readers should be familiar with Java, Scala, or Python. No knowledge of Spark or streaming operations is assumed, but some acquaintance with machine learning is helpful. ABOUT THE TECHNOLOGY Apache Spark is a big data processing framework perfect for analyzing near-real-time streams and discovering historical patterns in batched data sets. Spark also offers machine learning and graph processing capabilities.
£35.99
Manning Publications Data Science at Scale with Python and Dask
Book SynopsisLarge datasets tend to be distributed, non-uniform, and prone to change. Dask simplifies the process of ingesting, filtering, and transforming data, reducing or eliminating the need for a heavyweight framework like Spark. Data Science at Scale with Python and Dask teaches readers how to build distributed data projects that can handle huge amounts of data. The book introduces Dask Data Frames and teaches helpful code patterns to streamline the reader’s analysis. Key Features Working with large structured datasets Writing DataFrames Cleaningand visualizing DataFrames Machine learning with Dask-ML Working with Bags and Arrays Written for data engineers and scientists with experience using Python. Knowledge of the PyData stack (Pandas, NumPy, and Scikit-learn) will be helpful. No experience with low-level parallelism is required. About the technology Dask is a self-contained, easily extendible library designed to query, stream, filter, and consolidate huge datasets. Jesse Daniel has five years of experience writing applications in Python, including three years working with in the PyData stack (Pandas, NumPy, SciPy, Scikit-Learn). Jesse joined the faculty of the University of Denver in 2016 as an adjunct professor of business information and analytics, where he currently teaches a Python for Data Science course.
£35.99
Manning Publications Graph-Powered Machine Learning
Book SynopsisAt its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed as graphs. Graph-Powered Machine Learning introduces you to graph technology concepts, highlighting the role of graphs in machine learning and big data platforms. You’ll get an in-depth look at techniques including data source modeling, algorithm design, link analysis, classification, and clustering. As you master the core concepts, you’ll explore three end-to-end projects that illustrate architectures, best design practices, optimization approaches, and common pitfalls. Key Features · The lifecycle of a machine learning project · Three end-to-end applications · Graphs in big data platforms · Data source modeling · Natural language processing, recommendations, and relevant search · Optimization methods Readers comfortable with machine learning basics. About the technology By organizing and analyzing your data as graphs, your applications work more fluidly with graph-centric algorithms like nearest neighbor or page rank where it’s important to quickly identify and exploit relevant relationships. Modern graph data stores, like Neo4j or Amazon Neptune, are readily available tools that support graph-powered machine learning. Alessandro Negro is a Chief Scientist at GraphAware. With extensive experience in software development, software architecture, and data management, he has been a speaker at many conferences, such as Java One, Oracle Open World, and Graph Connect. He holds a Ph.D. in Computer Science and has authored several publications on graph-based machine learning.
£43.19
Manning Publications Machine Learning for Business: Using Amazon
Book Synopsis Imagine predicting which customers are thinking about switching to a competitor or flagging potential process failures before they happen Think about the benefits of automating tedious business processes and back-office tasks Consider the competitive advantage of making decisions when you know the most likely future events Machine learning can deliver these and other advantages to your business, and it’s never been easier to get started! Machine Learning for Business teaches you how to make your company more automated, productive, and competitive by mastering practical, implementable machine learning techniques and tools. Thanks to the authors’ down-to-earth style, you’ll easily grok why process automation is so important and why machine learning is key to its success. In this hands-on guide, you’ll work through seven end-to-end automation scenarios covering business processes in accounts payable, billing, payroll, customer support, and other common tasks. Using Amazon SageMaker (no installation required!), you’ll build and deploy machine learning applications as you practice takeaway skills you’ll use over and over. By the time you’re finished, you’ll confidently identify machine learning opportunities in your company and implement automated applications that can sharpen your competitive edge! Key Features Identifying processes suited to machine learning Using machine learning to automate back office processes Seven everyday business process projects Using open source and cloud-based tools Case studies for machine learning decision making For technically-inclined business professionals or business developers. No previous experience with automation tools or programming is necessary. Doug Hudgeon runs a business automation consultancy, putting his considerable experience helping companies set up automation and machine learning teams to good use. In 2000, Doug launched one of Australia’s first electronic invoicing automation companies. Richard Nichol has over 20 years of experience as a data scientist and software engineer. He currently specializes in maximizing the value of data through AI and machine learning techniques.
£26.99
Manning Publications Programmer's Guide to Apache Thrift
Book SynopsisProgrammer's Guide to Apache Thrift provides comprehensive coverage of the Apache Thrift framework along with a developer's-eye view of modern distributed application architecture. Packed with complete code examples and pragmatic discussion, this book lays the best practices for multi-language distributed application development. You'll take a guided tour through transports, protocols, IDL and servers as you explore complete example programs in C++, Java and Python. You'll also learn how to work with platforms ranging from enterprise servers to mobile clients. About the technology Any distributed application includes individual components, often written in different languages and hosted in multiple locations, which must communicate quickly and efficiently. Apache Thrift is a communication framework that enables cross-language remote procedure calls and serialization. Apache Thrift supports embedded, mobile, web, and server environments and a host of languages ranging from JavaScript to C++. It's perfect for back end services and embedded systems where size, scalability and performance are mission critical. Key Features Clear, concise coverage of all of the primary Apache Thrift features Complete coverage of the Apache Thrift Interface Definition Language Building and serializing complex user defined types Working with plug in serialization protocols and data compression Creating cross-language services Tools and features to enable interface evolution Randy Abernethy is an active Apache Thrift contributor and can be found on the dev and user email lists. A serial entrepreneur, Randy founded Hollywood's first all hard disk recording studio in the early 90s, a direct market access institutional brokerage in the 2000s, and has recently focused on the development of proprietary automated trading systems using Apache Thrift for interoperability.Table of ContentsPART 1 APACHE THRIFT OVERVIEW READ IN LIVEBOOK1. INTRODUCTION TO APACHE THRIFT 1.1. Polyglotism, the pleasure and the pain 1.2. Application integration with Apache Thrift 1.2.1. Type serialization 1.2.2. Service implementation 1.3. Building a simple service 1.3.1. The Hello IDL 1.3.2. The Hello server 1.3.3. A Python client 1.3.4. A C++ client 1.3.5. A Java client 1.4. The communications toolkit landscape 1.4.1. SOAP 1.4.2. REST 1.4.3. Protocol Buffers 1.4.4. Apache Avro 1.4.5. Strengths of Apache Thrift 1.4.6. Take away 1.5. Summary READ IN LIVEBOOK2. APACHE THRIFT ARCHITECTURE 2.1. Transports 2.1.1. The Transport interface 2.1.2. End point transports 2.1.3. Layered transports 2.1.4. Server transports 2.2. Protocols 2.3. Apache Thrift IDL 2.3.1. User-defined types and serialization 2.3.2. RPC services 2.4. Servers 2.5. Security 2.6. Summary READ IN LIVEBOOK3. BUILDING, TESTING, AND DEBUGGING 3.1. Installing the Apache Thrift IDL Compiler 3.1.1. Platform installers 3.1.2. VMs and containers 3.1.3. Building from source 3.2. The Apache Thrift source tree 3.3. Apache Thrift tests 3.4. Debugging RPC services 3.4.1. Examining packets on the wire 3.4.2. Unbuffered interfaces 3.4.3. Interface misalignment 3.4.4. I/O stack misalignment 3.4.5. Instrumenting code 3.4.6. Additional techniques 3.5. Summary PART 2 PROGRAMMING APACHE THRIFT READ IN LIVEBOOK4. MOVING BYTES WITH TRANSPORTS 4.1. End point transports ? part 1: memory & disk 4.1.1. Programming with memory transports 4.1.2. Programming with file transports 4.2. The transport interface 4.2.1. Basic transport operations 4.3. End point transports ? Part 2: networks 4.3.1. Network programming with TSocket 4.4. Server transports 4.4.1. Programming network servers with server transports 4.4.2. The Server Transport interface 4.5. Layered transports 4.5.1. Message framing 4.6. Summary READ IN LIVEBOOK5. SERIALIZING DATA WITH PROTOCOLS 5.1. Basic serialization with the binary protocol 5.1.1. Using the C++ TBinaryProtocol 5.1.2. Using the Java TBinaryProtocol 5.1.3. Using the Python TBinaryProtocol 5.1.4. Takeaway 5.2. The TProtocol interface 5.2.1. Apache Thrift serialization 5.2.2. C++ TProtocol 5.2.3. Java TProtocol 5.2.4. Python TProtocolBase 5.3. Serializing objects 5.3.1. Struct serialization 5.3.2. Struct deserialization 5.3.3. Struct evolution 5.4. TCompactProtocol 5.5. TJSONProtocol 5.6. Selecting a protocol 5.7. Summary READ IN LIVEBOOK6. APACHE THRIFT IDL 6.1. Interfaces 6.2. Apache Thrift IDL 6.2.1. IDL file names 6.2.2. Element names 6.2.3. Keywords 6.3. The IDL compiler 6.3.1. Compilation phases and error messages 6.3.2. Command line switches 6.4. Comments and documentation 6.5. Namespaces 6.6. Built-in types 6.6.1. Base types 6.6.2. Container types 6.6.3. Literals 6.7. Constants 6.7.1. C++ interface constant implementation 6.7.2. Java interface constant implementation 6.7.3. Python interface constant implementation
£47.99
Manning Publications Learn dbatools in a Month of Lunches
Book SynopsisAn effective DBA is an efficient DBA. And if you work with SQL Server, dbatools is a lifesaver. With over 500 commands, this free and open source PowerShell module has the horsepower to automate just about every task you can imagine—and then some! Learn dbatools in a Month of Lunches teaches you techniques that will make you more effective—and efficient—than you ever thought possible. Learn dbatools in a Month of Lunches is a practical hands-on guide to automating SQL Server with PowerShell and the awesome dbatools module. You'll master techniques you can immediately put into practice, from daily duties like backups and restores right through to performing security audits. Stabilize and standardize your SQL server environment, and simplify your tasks by building automation, alerting, and reporting with this powerful tool. Each lesson delivers another skill that you can use to speed through your core tasks as a SQL Server DBA! About the TechnologyWant to automate tasks for thousands of SQL servers at once? Want to migrate an entire SQL server using just the command line? dbatools can do all that—and more. A free and open source PowerShell module, dbatools offers over 500 commands for automating SQL Server from the command line. Boasting advanced options unavailable in official tools, dbatools makes it easy to automate tasks including mass exports for simplified disaster recovery, tempdb configuration, and improving an instance's security posture.Trade Review"This is an excellent resource to use for advancing your skills with advanced administration for SQL servers, regardless of the number of servers you are administering." Joseph Houghes "A great book that holds your hand on the journey from a beginner who has never used dbatools all the way to an expert!" Paul Broadwith "If you have not heard of dbatools, prepare to make managing your SQL Server infrastructure easier with the combination of it and PowerShell!" Wayne Mather "One of, if not THE best, technical books I have read, this book brings joy and life to automating DBA tasks through PowerShell, so much fun." Ben McNamara "This book and dbatools are a very serious game changer for doing automation, get out of the dark ages and look at these tools!" Steve Atchue "This book is a must for a busy SQL Server database professional." Arthur Zubarev
£51.49
Nova Science Publishers Inc Electronic Health Records: Interoperability Plans
Book SynopsisElectronic health records (EHRs) play an important role in optimizing the health care provided to active duty servicemembers and veterans. When a servicemember leaves military service by way of discharge, separation, or retirement he or she may become eligible for VA benefits and services including VA health care. Transitioning their health care information from one large health care system (Department of Defense; DOD) to the other (Department of Veterans Affairs; VA) involves coordination of data and information between DOD and VA. Longstanding concern that this exchange be effective has been expressed in many quarters, including Congress. The purpose of this book is to provide a background on the long-standing efforts in sharing health information between DOD and VA. The book also describes changes to the integrated electronic health record system and evaluates the departments'' current plans; and determines whether the departments are effectively collaborating on management of the program.
£63.74
Nova Science Publishers Inc Air Transport Safety: An Introduction
Book SynopsisThis book is composed of thirteen chapters. Chapter 1 provides a short overview of the Air Transport System, from both the micro- and macro-level structure. It covers the descriptions and definitions of the main system elements: air carriers, airports and air navigation service providers, as well as personnel, equipment, procedures and the environment. Chapter 2 introduces the reader to the basic concepts in air transport risk and safety. This chapter covers the definitions of safety, hazards, risk, incidents and accidents. It further explains safety criteria, safety barriers, safety regulatory requirements, and finally it compares Safety I and Safety II concepts. Chapter 3 covers the field of Air Transport Safety Metrics and Records. Here safety metrics, accident statistics and safety records are explained and illustrated. Finally, a safety comparison of transport modes is made. Chapter 4 presents Sources of Accident/Incident Information. Explained here is how safety-related events (incidents and accidents) are investigated and what the phases of the investigation process are, as well as how safety information is collected. Chapter 5 describes the main safety issues in contemporary air transport. They are grouped into three sets: airport, air navigation service providers and air carriers'' safety issues.
£159.74
Manning Publications Introducing Data Science
Book Synopsis DESCRIPTION Data Science has become one of the hottest fields in technology. Firms worldwide are scrambling to find developers with data science skills to work on projects ranging from social media marketing to machine learning, but the prerequisite knowledge and experience for this career can seem bewildering. This book is designed to help anyone who wants to learn more about data science get started. Introducing Data Science teaches readers how to accomplish the fundamental tasks that occupy data scientists. They’ll use the Python language and common Python libraries as they experience firsthand the challenges of dealing with data at scale. They’ll discover how Python allows them to gain insights from huge data sets that need to be stored on multiple machines, or for data moving at such speed no single machine can handle it. After reading this book, readers will have a solid foundation to consider a career in data science. KEY SELLING POINTS Master big data with Python and become a data scientist How to use data science in a big data world Gain hands on experience with the most common Python data science libraries AUDIENCE This book assumes readers (software engineers, business intelligence reporters, database moderators, statisticians, web developers, anyone interested in Big Data) are comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required. ABOUT THE TECHNOLOGY At its core, data science is a set of concepts and techniques for extracting meaning and clarity from enormous stored data sets or fast-moving data streams. Data scientists write programs to interpret these data. The Python programming language is a favorite tool of data scientists because it's easy to read and write, and it provides several high-value libraries that simplify core tasks like statistics, machine learning algorithms, and mathematics.
£35.99
Manning Publications MongoDB in Action Second Edition
Book Synopsis
£50.99
Manning Publications Essential Graphrag
Book Synopsis
£36.67
Manning Publications PostgreSQL Mistakes and How to Avoid Them
Book Synopsis
£37.49
Manning Publications Cloud Observability in Action
Book SynopsisGenerate actionable insights about your cloud-native systems. For developers and SREs who have worked with cloud-native applications. This book is suitable for any public cloud. In Cloud Observability in Action, you will learn how to set up an observability system that learns from a cloud application's signals, logging, and monitoring using free and open-source tools. You will learn, among others, how to: Apply observability in cloud native systems Understand observability signals, including their costs and benefits Apply good practices around instrumentation and signal collection Deliver dashboarding, alerting, and SLOs/SLIs at scale Choose the correct signal types for given roles or tasks Pick the right observability tool for any given function Communicate the benefits of observability to management Cloud-native, serverless, and containerised applications are made of hundreds of moving parts. When something goes wrong, it's not enough to just know there is a problem—you need to know where it is, what it is, and even how to fix it. Cloud Observability in Action shows you how to go beyond traditional monitoring and build observability systems that turn application telemetry into actionable insight. About the technology A well-designed observability system provides insight into bugs and performance issues in cloud-native applications. Often, observability is the difference between an error message and an explanation! You know exactly which service is affected, who's responsible for its repair, and even how it can be optimised in the future. Best of all, observability allows you to easily automate your error handling with machine users applying fixes without any human help.
£45.99
Manning Publications Data Mesh in Action
Book SynopsisRevolutionize the way your organization approaches data with a data mesh! This new decentralized architecture outpaces monolithic lakes and warehouses and can work for a company of any size. Data Mesh in Action reveals how this ground breaking architecture looks for both small start-ups and large enterprises. You'll see a datamesh in action as you explore both an extended case study andmultiple real-world examples. As you go, you'll be expertly guidedthrough discussions around Socio-Technical Architecture and Domain-Driven Design with the goal of building a sleek data-as-a-productsystem.
£45.04
Technics Publications LLC Versión en español de la Guía DAMA de los
Book SynopsisText in Spanish.
£40.79
Technics Publications LLC Data Resource Understanding: Utilizing the Data
Book SynopsisAre you struggling to understand the data you need to support your business activities? Are you frustrated over data that do not answer your questions or provide the wrong answers to your questions? Are you worried that your organisation is not adequately supporting its citizens or customers? Are you concerned over civil or criminal liability for the quality and use of your data? If the answer to any of these questions is Yes, they you need to read "Data Resource Understanding" to help you and everyone in your organisation thoroughly understand the data they need to support the business activities. Most public and private sector organisations have no formal method for thoroughly understanding the data needed to support their business activities. They seldom have a method that begins with the organisation''s perception of the business world and continues through a formal Data Resource Development Cycle to produce a high quality, thoroughly understood data resource that fully supports the organisation''s current and future business information demand. Data Resource Data provided the complete detailed data resource model for understanding and managing data as a critical resource of the organisation. Data Resource Understanding is the companion book to Data Resource Data. It provides a detailed explanation of how to thoroughly understand an organisation''s data resource and to document that understanding with Data Resource Data. Together they provide an organisation with the foundation for properly managing their data as a critical resource. Like in "Data Resource Simplexity", Michael Brackett draws on over half a century of data management experience, in a wide variety of different public and private sector organisations, to understand and document an organisation''s data resource. He leverages theories, concepts, principles, and techniques from many different and varied disciplines, such as human dynamics, mathematics, physics, chemistry, philosophy, and biology, and applies them to the process of formally documenting an organisation''s data resource.
£32.79
Pragmatic Bookshelf Seven Databases in Seven Weeks 2e: A Guide to
Book SynopsisData is getting bigger and more complex by the day, and so are your choices in handling it. Explore some of the most cutting-edge databases available - from traditional relational databases to newer NoSQL approaches - and make informed decisions about challenging data storage problems. This is the only comprehensive guide to the world of NoSQL databases, with in-depth practical and conceptual introductions to seven different technologies: Redis, Neo4J, CouchDB, MongoDB, HBase, Postgres, and DynamoDB. This second edition includes a new chapter on DynamoDB and updated content for each chapter. While relational databases such as MySQL remain as relevant as ever, the alternative, NoSQL paradigm has opened up new horizons in performance and scalability and changed the way we approach data-centric problems. This book presents the essential concepts behind each database alongside hands-on examples that make each technology come alive. With each database, tackle a real-world problem that highlights the concepts and features that make it shine. Along the way, explore five database models - relational, key/value, columnar, document, and graph - from the perspective of challenges faced by real applications. Learn how MongoDB and CouchDB are strikingly different, make your applications faster with Redis and more connected with Neo4J, build a cluster of HBase servers using cloud services such as Amazon's Elastic MapReduce, and more. This new edition brings a brand new chapter on DynamoDB, updated code samples and exercises, and a more up-to-date account of each database's feature set. Whether you're a programmer building the next big thing, a data scientist seeking solutions to thorny problems, or a technology enthusiast venturing into new territory, you will find something to inspire you in this book. What You Need: You'll need a *nix shell (Mac OS or Linux preferred, Windows users will need Cygwin), Java 6 (or greater), and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.
£36.57
The Pragmatic Programmers Exploring Graphs with Elixir: Connect Data with
Book SynopsisData is everywhere - it's just not very well connected, which makes it super hard to relate dataset to dataset. Using graphs as the underlying glue, you can readily join data together and create navigation paths across diverse sets of data. Add Elixir, with its awesome power of concurrency, and you'll soon be mastering data networks. Learn how different graph models can be accessed and used from within Elixir and how you can build a robust semantics overlay on top of graph data structures. We'll start from the basics and examine the main graph paradigms. Get ready to embrace the world of connected data! Graphs provide an intuitive and highly flexible means for organizing and querying huge amounts of loosely coupled data items. These data networks, or graphs in math speak, are typically stored and queried using graph databases. Elixir, with its noted support for fault tolerance and concurrency, stands out as a language eminently suited to processing sparsely connected and distributed datasets. Using Elixir and graph-aware packages in the Elixir ecosystem, you'll easily be able to fit your data to graphs and networks, and gain new information insights. Build a testbed app for comparing native graph data with external graph databases. Develop a set of applications under a single umbrella app to drill down into graph structures. Build graph models in Elixir, and query graph databases of various stripes - using Cypher and Gremlin with property graphs and SPARQL with RDF graphs. Transform data from one graph modeling regime to another. Understand why property graphs are especially good at graph traversal problems, while RDF graphs shine at integrating different semantic models and can scale up to web proportions. Harness the outstanding power of concurrent processing in Elixir to work with distributed graph datasets and manage data at scale. What You Need: To follow along with the book, you should have Elixir 1.10+ installed. The book will guide you through setting up an umbrella application for a graph testbed using a variety of graph databases for which Java SDK 8+ is generally required. Instructions for installing the graph databases are given in an appendix.
£36.57
