Relational databases Books

Book SynopsisTeach database theory with the bestselling text on the subject Database Systems: A Practical Approach to Design, Implementation, and Management introduces the theory behind databases in a concise yet comprehensive manner. Designed for undergraduate courses, the text is accessible for non-technical readers. This title comes with a Companion Website.Table of ContentsPart 1 Background Chapter 1 Introduction to Databases Database Environment Database Architectures and the Web Part 2 The Relational Model and Languages Chapter 4 The Rational Model Chapter 5 Relational Algebra and Relational Calculus Chapter 6 SQL: Data Manipulation Chapter 7 SQL: Data Definition Chapter 8 Advanced SQL Chapter 9 Object-Relational DBMSs Part 3 Database Analysis and Design Chapter 10 Database System Development Lifecycle Chapter 11 Database Analysis and the DreamHome Case Study Chapter 12 Entity-Relationship Modeling Chapter 13 Enhanced Entity-Relationship Modeling Chapter 14 Normalization Chapter 15 Advanced Normalization Part 4 Methodology Chapter 16 Methodology – Conceptual Database Design Chapter 17 Methodology – Logical Database Design for the Relational Model Chapter 18 Methodology – Physical Database Design for Relational Databases Chapter 19 Methodology – Monitoring and Tuning the Operational System Part 5 Selected Database Issues Chapter 20 Security and Administration Chapter 21 Professional, Legal, and Ethical Issues in Data Management Chapter 22 Transaction Management Chapter 23 Query Processing Part 6 Distributed DBMSs and Replication Chapter 24 Distributed DBMSs – Concepts and Design Chapter 25 Distributed DBMSs – Advanced Concepts Chapter 26 Replication and Mobile Databases Part 7 Object DBMSs Chapter 27 Object-Oriented DBMSs – Concepts and Design Chapter 28 Object-Oriented DBMSs – Standard Systems Part 8 The Web and DBMSs Chapter 29 Web Technology and DBMSs Chapter 30 Semistructured Data and XML Part 9 Business Intelligence Chapter 31 Data Warehousing Concepts Chapter 32 Data Warehousing Design Chapter 33 OLAP Chapter 34 Data Mining Appendices References Further Reading Index

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Book SynopsisThe field of artificial intelligence, data science, and analytics is crippling itself. Exaggerated promises of unrealistic technologies, simplifications of complex projects, and marketing hype are leading to an erosion of trust in one of our most critical approaches to making decisions: data driven.This book aims to fix this by countering the AI hype with a dose of realism. Written by two experts in the field, the authors firmly believe in the power of mathematics, computing, and analytics, but if false expectations are set and practitioners and leaders don't fully understand everything that really goes into data science projects, then a stunning 80% (or more) of analytics projects will continue to fail, costing enterprises and society hundreds of billions of dollars, and leading to non-experts abandoning one of the most important data-driven decision-making capabilities altogether.For the first time, business leaders, practitioners, students, and interes

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Book SynopsisJump-start your career as a data scientistlearn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that's dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. This guide for data scientists differs from other instructional guides on the subject. It doesn't cover SQL broadly. Instead, you'll learn the subset of SQL skills that data analysts and data scientists use frequently. You'll also gain practical advice and direction on how to think about constructing your dataset. Gain an understanding of relational database structure, query design, and SQL syntaxDevelop queries to construct datasets for use in applications like interactive reports and machine learning algorithmsReview strategies and approaches so you can design analytical datasetsPractice your techniques with the provided database and SQL code In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner's perspective, moving your data scientist career forward! Table of ContentsIntroduction xix Chapter 1 Data Sources 1 Data Sources 1 Tools for Connecting to Data Sources and Editing SQL 2 Relational Databases 3 Dimensional Data Warehouses 7 Asking Questions About the Data Source 9 Introduction to the Farmer’s Market Database 11 A Note on Machine Learning Dataset Terminology 12 Exercises 13 Chapter 2 The SELECT Statement 15 The SELECT Statement 15 The Fundamental Syntax Structure of a SELECT Query 16 Selecting Columns and Limiting the Number of Rows Returned 16 The ORDER BY Clause: Sorting Results 18 Introduction to Simple Inline Calculations 20 More Inline Calculation Examples: Rounding 22 More Inline Calculation Examples: Concatenating Strings 24 Evaluating Query Output 26 SELECT Statement Summary 29 Exercises Using the Included Database 30 Chapter 3 The WHERE Clause 31 The WHERE Clause 31 Filtering SELECT Statement Results 32 Filtering on Multiple Conditions 34 Multi-Column Conditional Filtering 40 More Ways to Filter 41 BETWEEN 41 IN 42 LIKE 43 IS NULL 44 A Warning About Null Comparisons 44 Filtering Using Subqueries 46 Exercises Using the Included Database 47 Chapter 4 CASE Statements 49 CASE Statement Syntax 50 Creating Binary Flags Using CASE 52 Grouping or Binning Continuous Values Using CASE 53 Categorical Encoding Using CASE 56 CASE Statement Summary 59 Exercises Using the Included Database 60 Chapter 5 SQL JOINs 61 Database Relationships and SQL JOINs 61 A Common Pitfall when Filtering Joined Data 71 JOINs with More than Two Tables 74 Exercises Using the Included Database 76 Chapter 6 Aggregating Results for Analysis 79 GROUP BY Syntax 79 Displaying Group Summaries 80 Performing Calculations Inside Aggregate Functions 84 MIN and MAX 88 COUNT and COUNT DISTINCT 90 Average 91 Filtering with HAVING 93 CASE Statements Inside Aggregate Functions 94 Exercises Using the Included Database 96 Chapter 7 Window Functions and Subqueries 97 ROW NUMBER 98 RANK and DENSE RANK 101 NTILE 102 Aggregate Window Functions 103 LAG and LEAD 108 Exercises Using the Included Database 111 Chapter 8 Date and Time Functions 113 Setting datetime Field Values 114 EXTRACT and DATE_PART 115 DATE_ADD and DATE_SUB 116 DATEDIFF 118 TIMESTAMPDIFF 119 Date Functions in Aggregate Summaries and Window Functions 119 Exercises 126 Chapter 9 Exploratory Data Analysis with SQL 127 Demonstrating Exploratory Data Analysis with SQL 128 Exploring the Products Table 128 Exploring Possible Column Values 131 Exploring Changes Over Time 134 Exploring Multiple Tables Simultaneously 135 Exploring Inventory vs. Sales 138 Exercises 142 Chapter 10 Building SQL Datasets for Analytical Reporting 143 Thinking Through Analytical Dataset Requirements 144 Using Custom Analytical Datasets in SQL: CTEs and Views 149 Taking SQL Reporting Further 153 Exercises 157 Chapter 11 More Advanced Query Structures 159 UNIONs 159 Self-Join to Determine To-Date Maximum 163 Counting New vs. Returning Customers by Week 167 Summary 171 Exercises 171 Chapter 12 Creating Machine Learning Datasets Using SQL 173 Datasets for Time Series Models 174 Datasets for Binary Classification 176 Creating the Dataset 178 Expanding the Feature Set 181 Feature Engineering 185 Taking Things to the Next Level 189 Exercises 189 Chapter 13 Analytical Dataset Development Examples 191 What Factors Correlate with Fresh Produce Sales? 191 How Do Sales Vary by Customer Zip Code, Market Distance, and Demographic Data? 211 How Does Product Price Distribution Affect Market Sales? 217 Chapter 14 Storing and Modifying Data 229 Storing SQL Datasets as Tables and Views 229 Adding a Timestamp Column 232 Inserting Rows and Updating Values in Database Tables 233 Using SQL Inside Scripts 236 In Closing 237 Exercises 238 Appendix Answers to Exercises 239 Index 255

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Book SynopsisTable of ContentsIntroduction xxvii Chapter 1 • Stages of an Implementation Overview 1 What Is Microsoft Dynamics? 1 The Client Journey 2 Implementation Methodologies 5 Waterfall and Sure Step 5 Agile and Scrum 7 Triple Constraints 8 The Bottom Line 9 Chapter 2 • What to Do Before You Begin a Project 11 Identify Your Project Team and Stakeholders 11 Executive Sponsor 12 Project Owner 12 Business Process Owner(s) 13 Project Manager 13 Core Team and a Core Team Lead 14 Subject Matter Experts 14 IT Resources 15 Time Commitment by Role 17 Identify Your Processes in Scope 18 Clean Up Your Data 19 Identify Your “Master” Data 19 Develop Naming Conventions 20 Identify System Owners 20 Find and Resolve Duplicates and Incorrect Data 20 Define Your Success Metrics 21 Possible Benefits 22 Building Your Business Case and Securing Funding 23 How Much Should an ERP Project Cost? 24 Costs to Include in Your Calculations 24 Capitalizing Costs 25 Contingency 27 Return on Investment (ROI) 27 Gaining Approval 28 The Bottom Line 29 Chapter 3 • Four Keys to Consider When Buying an ERP or CRM Solution 31 Selection Process 31 Selection Consultant 32 Decision Maker 33 The Four Keys 33 Fit 34 Platform 35 Implementer 39 Cost 41 Building Your Scorecard 44 The Bottom Line 45 Chapter 4 • How to Evaluate and Buy Business Application Software 47 Buying Process Steps 47 Qualification Stage 48 Discovery and Demonstration Stage 49 Selecting Your Vendor 51 Leadership or Board Approval 54 Moving Forward 54 The Bottom Line 54 Chapter 5 • Organizing Your Team for Success and Project Governance 57 RACI 57 Your Project Team 58 Your Partner’s Implementation Team 59 Executive Sponsor 60 Engagement Manager 60 Project Manager 60 Solution Architect or Solution Delivery Manager 60 Functional Consultant or Consultants 61 Technical Consultant 61 Development Lead and Developers 61 Integration Architect 61 Data Migration Specialist 62 Project Governance 62 Project Communication 62 Resource Loading 62 Project Schedule 66 Document Repository 67 Budget Tracking 68 Change Requests 68 Project Management Plan 68 The Bottom Line 69 Chapter 6 • Sprints and Tools Needed to Run Your Project 73 Definition of a Sprint 73 Length of a Sprint 74 Start and End of a Sprint 74 Delivering Value in a Sprint 74 Backlog 75 Project Backlog 75 Sprint Backlog 76 Allocating Work to Team Members 76 Sprint Success Rate 76 Sprint Meetings 77 Sprint Planning 77 Sprint Review 77 Sprint Retrospective 78 Stand-up Meetings 78 Work Definitions 79 Epic 79 Feature 79 User Story 80 Requirement 80 Research Task 80 Design Task 80 Development Task 81 Test Task 81 Other Task 81 Test Case 81 Test 81 Bug (Defect) 81 Risk 81 Issue 82 Change Request 82 Code and Changesets 82 Azure DevOps 82 DevOps Fields 82 Progress Reporting 83 Analytical Views 83 The Bottom Line 84 Chapter 7 • Change Management Throughout Your Project 87 Success Criteria 88 Use of Satisfaction Surveys 89 Nine Steps to Change Management 90 Leadership Alignment 90 Organization Evaluation 91 Outline Your Business Process Change Steps 92 Develop a System Vision that Provides Benefits to All Stakeholders 92 Communicate Effectively 92 Maximize the Team’s Time in the New System 94 Train Effectively 94 Set Realistic Expectations for the System Just After Go-Live 94 Support Your Team Members After Go-Live 95 Steps to Business Process Change 95 Importance of Adoption 96 The Bottom Line 96 Chapter 8 • Organizing Your Business by Processes 99 Common Language Businesses Speak 99 Operations 100 Sales 100 Finance and Administration 100 Standard Processes 100 Process Hierarchy 102 Process Category 102 Process Group 103 Process 103 Sub-processes, Tasks, Activities, and Requirements 104 Discovering Your Processes 104 SIPOC 104 Core Team Members 106 Rounding Out Your Scope 106 The Bottom Line 106 Chapter 9 • Independent Software Vendors—Filling Gaps and Managing Partnerships 109 The Purpose of ISVs 109 Hosting Providers 110 Private Hosting 111 SaaS-Style Hosting 111 Industry ISVs 111 Deciding If You Need an Industry ISV 112 Functional ISVs 113 Missing Functionality 113 Advanced Features 113 Missing Connector 113 Automation 114 Reporting Extensions 114 Deciding If You Need a Functional ISV 114 Working with ISVs 114 Budgeting for ISV Solutions 115 Implementation Partner or Customer Managed 115 Buying the ISV License or Subscription 115 Implementation of ISV Products 116 Manage Your ISV Projects Closely 116 Microsoft’s AppSource Marketplace 117 Product Listing 118 Services Listing 118 The Bottom Line 119 Chapter 10 • Factors for a Successful Project Kickoff 121 Pre-Kickoff Meeting Activities 121 Checklist 121 Expectations for the Meeting 124 Outing 124 Kickoff Meeting Content 124 Executive Overview 125 Introductions and Role Review 125 Expectations for Team Members 126 Project Management and Communication Plan 126 Project Schedule 126 Resources 126 Navigation Overview [Optional] 127 Wrapping Up 127 Executive Message 127 Expectations for the Project Team 128 Time Commitment 128 Decision-Making 129 Power of Positivity 129 The Bottom Line 130 Chapter 11 • Designing the Software Collaboratively 133 Joint Application Design Concept 133 Joint Process Design and Other Design-Related Definitions 134 What Is a Joint Process Design (JPD) Session? 134 Happy Path 136 “As-Is” vs “To Be” 136 Joint Process Design Iterations 137 JPD1 137 JPD2 139 JPD3 140 JPD4 140 Keys to Successful JPDs 140 JPD Output 141 SIPOC 142 The Bottom Line 143 Chapter 12 • Requirements Gathering and Staying “In the Box” 145 Staying in the Box 145 Customization vs In-the-Box Examples 146 Requirements 147 Out-of-the-Box Fields as Requirements 147 Requirements Link to Processes 148 Functional vs Non-functional Requirements 149 Verifying Requirements 150 Writing Good Requirements 150 Requirements Tips 150 Fit/Gap Analysis 151 Fit/Gap Spreadsheet 152 Trade-Offs 153 The Cost of Customizations 154 Cloud vs On-Premise Software 155 The Bottom Line 155 Chapter 13 • Conference Room Pilots 157 The Purpose of a Conference Room Pilot 157 How to Organize CRPs 158 Common Elements of CRPs 159 CRP Agenda 159 Logistics 160 Issues and Questions 160 CRP Roles and Responsibilities 161 Session Leader 161 Helper/Expert 162 Business Process Owner 162 Users/Students 162 Who Not to Invite 163 CRP Place in the Overall Schedule 163 Can You Do a CRP on One Process Group at the Same Time That You Do a JPD? 164 Entrance Criteria 164 CRP vs UAT 166 How They Are Similar 166 How They Are Different 166 What to Do Between CRP and the End of the Create Stage 167 CRP Goals 168 The Bottom Line 168 Chapter 14 • Dealing with Challenges Mid-Project 171 Managing the Project Status 172 Status Report 172 Colors on a Status Report 173 Managing Your Budget 175 Project Pulse 177 Risks and Issues 177 Risk Register 178 Issues vs Bugs 179 Common Project Challenges 179 The Bottom Line 183 Chapter 15 • Customizations vs Configurations and How You Manage Them 185 Customizations vs Configurations 185 Customization 185 Configuration 186 Integration 186 Master Data 187 Metadata 187 Personalization 187 Reference Data 187 When to Customize vs Configure 188 Why Choose to Customize 188 Tracking Configurations 188 Configuration Tracker 189 Gold Environment 189 Lifecycle Services 189 Functional Design Documents 190 Overview 190 Modification 190 Testing 190 Development Quotation 191 Revision and Sign-off 191 Updates 191 Design Complete 191 The Development Process 192 Develop the Solution 192 Unit Test 192 Code Review 193 Functional Testing (Part 1) 193 Finishing Up 194 After Code Complete 194 Deploying the Code 194 Functional Testing (Part 2) 194 Preparing for CRP and UAT 195 The Lifecycle of a Customization 195 Managing These Tasks 195 Wrap-Up 196 The Bottom Line 197 Chapter 16 • Data Migration—Early and Often 199 Data Migration Plan 200 Proactive Cleaning 200 Before the Kickoff 201 Data Migration Tool 202 Iterations 203 Extract 206 Finding the Data 206 Extraction Tools 206 Transform 208 Mapping the Data 208 Mapping Tools 208 Transforming Mapped Data 209 Load 210 Order of Operation 210 Load Time 210 Validating the Data 210 Technical Validation 211 Business Validation 211 Functional Validation 212 Go-Live Iteration 212 The Bottom Line 213 Chapter 17 • Environment Management and Deployments 215 Types of Environments 216 Developer Environments 216 Build 217 Test 217 Sandbox 218 Production 219 Environment Plan 220 Types of Releases 220 Frequency of Code Moves 222 Populating Configurations and Master Data 222 Deploying Code 223 Application Lifecycle Management 223 Environment Flow Using DevOps 224 Rollback 224 Security 225 Definitions 225 How Best to Manage 226 The Bottom Line 227 Chapter 18 • Testing 229 Definitions 229 Types of Testing 230 Common Testing Terms 231 Pre-Deploy Stage Activities 232 Testing Strategy 232 Unit Test and Regression Tests 233 Developing Test Cases 234 UAT Entrance Criteria 235 UAT Exit Criteria 236 UAT Sessions 236 Purpose 236 Additional Benefits of UAT Sessions 237 UAT Roles and Responsibilities 237 Executing Your Test Plans 238 Tips for the Sessions 239 Post UAT Testing 240 Issues List 241 Process Sign-Offs 241 Scenario Recaps 241 The Bottom Line 242 Chapter 19 • Training for All 245 Learning During Interactive Sessions 246 JPDs 246 CRPs 246 UAT 247 Learning Modalities 247 In-Person, Classroom Style 248 Remote, Synchronous Training 249 Asynchronous 251 Building Your Training Content 251 End User Training Content 251 Product Help Content 252 Microsoft Learn 253 Recording Sessions 253 Task Recorder 253 How Much to Document 254 How to Manage and Distribute Your Content 254 Learning Management Systems 255 Building Your End User Training Schedule 255 Pre-Training Learning 256 Train the Trainer 256 Synchronous Sessions 257 Advanced Concepts 257 Testing Users’ Knowledge 257 Office Hours 258 The Bottom Line 259 Chapter 20 • Going Live 261 Go-Live Criteria 261 Cutover Plan 262 Bug Criteria 262 Data Migration and Security Criteria 263 Support Readiness 264 Training Review 264 Communication Plan 265 Go-Live Scorecard 265 Mock Cutover and Final Week Activities 266 Disaster Recovery 267 System Setup Before Cutover 267 Go/No-Go Meetings 268 When to Have It 268 Voting Criteria 268 Meeting Agenda 269 Order and Outcome of the Votes 269 Next Steps 270 Live Cutover 270 Impact of the Cutover Start Timing 271 Completing Cutover Activities 271 Rollback Plan 272 Acknowledge the Team 272 The Bottom Line 272 Chapter 21 • Hypercare 275 Go-Live Support 275 Day 1 276 Week 1 276 Project Change Champions 277 Prioritizing Issues 277 Weeks 2–4 278 First Month End 278 Duration of Hypercare 279 Role of HelpDesk 279 Sample SLA 280 Project Team Support 280 Support Levels 281 Refer Users to Training 283 Making the Transition to HelpDesk Later 283 Post Go-Live Releases 284 Planning for Future Releases 285 Hotfix Release 285 Scheduled Releases 286 Project Team Transition 287 Rolling Off the Project Team 287 Documentation 288 Expectations of Support 288 After the Transition 289 The Bottom Line 289 Chapter 22 • Support and Enhance Your Project 291 Support After Hypercare 291 Extending the Transition from Consulting to Support 292 Engaging Your Partner for Support 292 Microsoft and ISV Support Plans 294 After Action Review 295 Who to Invite 295 How to Run the Meeting 296 What to Do with the Feedback 297 Ongoing Releases 297 Microsoft Dynamics 365 Release Cadence 297 Release Testing 297 When to Schedule Your Releases 298 What to Include in Releases 299 Future Enhancements 299 New Functionality 299 Usability 300 Guardrails 301 Business Intelligence 301 Incorporating Dynamics Data into Your Daily Business 302 Integrations 302 Machine Learning and Artificial Intelligence 302 Calculating Return on Investment 303 ROI Checkpoints 304 The Bottom Line 305 Chapter 23 • Bringing It All Together 307 Align Stage 307 Define Stage 308 Create Stage 311 Deploy Stage 313 Empower Stage 314 Additional Resources 315 The Bottom Line 315 Appendix • The Bottom Line 317 Chapter 1: Stages of an Implementation Overview 317 Chapter 2: What to Do Before You Begin a Project 318 Chapter 3: Four Keys to Consider When Buying an ERP or CRM Solution 320 Chapter 4: How to Evaluate and Buy Business Application Software 322 Chapter 5: Organizing Your Team for Success and Project Governance 323 Chapter 6: Sprints and Tools Needed to Run Your Project 325 Chapter 7: Change Management Throughout Your Project 326 Chapter 8: Organizing Your Business by Processes 328 Chapter 9: Independent Software Vendors—Filling Gaps and Managing Partnerships 329 Chapter 10: Factors for a Successful Project Kickoff 331 Chapter 11: Designing the Software Collaboratively 332 Chapter 12: Requirements Gathering and Staying “In the Box” 334 Chapter 13: Conference Room Pilots 335 Chapter 14: Dealing with Challenges Mid-Project 337 Chapter 15: Customizations vs Configurations and How You Manage Them 338 Chapter 16: Data Migration—Early and Often 340 Chapter 17: Environment Management and Deployments 341 Chapter 18: Testing 343 Chapter 19: Training for All 344 Chapter 20: Going Live 346 Chapter 21: Hypercare 347 Chapter 22: Support and Enhance Your Project 349 Chapter 23: Bringing It All Together 350 Glossary 353 Index 369

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Book SynopsisA complete guide to Pentaho Kettle, the Pentaho Data lntegration toolset for ETL This practical book is a complete guide to installing, configuring, and managing Pentaho Kettle. If you're a database administrator or developer, you'll first get up to speed on Kettle basics and how to apply Kettle to create ETL solutionsbefore progressing to specialized concepts such as clustering, extensibility, and data vault models. Learn how to design and build every phase of an ETL solution. Shows developers and database administrators how to use the open-source Pentaho Kettle for enterprise-level ETL processes (Extracting, Transforming, and Loading data) Assumes no prior knowledge of Kettle or ETL, and brings beginners thoroughly up to speed at their own pace Explains how to get Kettle solutions up and running, then follows the 34 ETL subsystems model, as created by the Kimball Group, to explore the entire ETL lifecycle, including all aspects of data warehoTable of ContentsIntroduction xxxi Part I Getting Started 1 Chapter 1 ETL Primer 3 OLTP versus Data Warehousing 3 What Is ETL? 5 The Evolution of ETL Solutions 5 ETL Building Blocks 7 ETL, ELT, and EII 8 ELT 9 EII: Virtual Data Integration 10 Data Integration Challenges 11 Methodology: Agile BI 12 ETL Design 14 Data Acquisition 14 Beware of Spreadsheets 15 Design for Failure 15 Change Data Capture 16 Data Quality 16 Data Profiling 16 Data Validation 17 ETL Tool Requirements 17 Connectivity 17 Platform Independence 18 Scalability 18 Design Flexibility 19 Reuse 19 Extensibility 19 Data Transformations 20 Testing and Debugging 21 Lineage and Impact Analysis 21 Logging and Auditing 22 Summary 22 Chapter 2 Kettle Concepts 23 Design Principles 23 The Building Blocks of Kettle Design 25 Transformations 25 Steps 26 Transformation Hops 26 Parallelism 27 Rows of Data 27 Data Conversion 29 Jobs 30 Job Entries 31 Job Hops 31 Multiple Paths and Backtracking 32 Parallel Execution 33 Job Entry Results 34 Transformation or Job Metadata 36 Database Connections 37 Special Options 38 The Power of the Relational Database 39 Connections and Transactions 39 Database Clustering 40 Tools and Utilities 41 Repositories 41 Virtual File Systems 42 Parameters and Variables 43 Defining Variables 43 Named Parameters 44 Using Variables 44 Visual Programming 45 Getting Started 46 Creating New Steps 47 Putting It All Together 49 Summary 51 Chapter 3 Installation and Configuration 53 Kettle Software Overview 53 Integrated Development Environment: Spoon 55 Command-Line Launchers: Kitchen and Pan 57 Job Server: Carte 57 Encr.bat and encr.sh 58 Installation 58 Java Environment 58 Installing Java Manually 58 Using Your Linux Package Management System 59 Installing Kettle 59 Versions and Releases 59 Archive Names and Formats 60 Downloading and Uncompressing 60 Running Kettle Programs 61 Creating a Shortcut Icon or Launcher for Spoon 62 Configuration 63 Configuration Files and the .kettle Directory 63 The Kettle Shell Scripts 69 General Structure of the Startup Scripts 70 Adding an Entry to the Classpath 70 Changing the Maximum Heap Size 71 Managing JDBC Drivers 72 Summary 72 Chapter 4 An Example ETL Solution—Sakila 73 Sakila 73 The Sakila Sample Database 74 DVD Rental Business Process 74 Sakila Database Schema Diagram 75 Sakila Database Subject Areas 75 General Design Considerations 77 Installing the Sakila Sample Database 77 The Rental Star Schema 78 Rental Star Schema Diagram 78 Rental Fact Table 79 Dimension Tables 79 Keys and Change Data Capture 80 Installing the Rental Star Schema 81 Prerequisites and Some Basic Spoon Skills 81 Setting Up the ETL Solution 82 Creating Database Accounts 82 Working with Spoon 82 Opening Transformation and Job Files 82 Opening the Step’s Configuration Dialog 83 Examining Streams 83 Running Jobs and Transformations 83 The Sample ETL Solution 84 Static, Generated Dimensions 84 Loading the dim_date Dimension Table 84 Loading the dim_time Dimension Table 86 Recurring Load 87 The load_rentals Job 88 The load_dim_staff Transformation 91 Database Connections 91 The load_dim_customer Transformation 95 The load_dim_store Transformation 98 The fetch_address Subtransformation 99 The load_dim_actor Transformation 101 The load_dim_film Transformation 102 The load_fact_rental Transformation 107 Summary 109 Part II ETL 111 Chapter 5 ETL Subsystems 113 Introduction to the 34 Subsystems 114 Extraction 114 Subsystems 1–3: Data Profiling, Change Data Capture, and Extraction 115 Cleaning and Conforming Data 116 Subsystem 4: Data Cleaning and Quality Screen Handler System 116 Subsystem 5: Error Event Handler 117 Subsystem 6: Audit Dimension Assembler 117 Subsystem 7: Deduplication System 117 Subsystem 8: Data Conformer 118 Data Delivery 118 Subsystem 9: Slowly Changing Dimension Processor 118 Subsystem 10: Surrogate Key Creation System 119 Subsystem 11: Hierarchy Dimension Builder 119 Subsystem 12: Special Dimension Builder 120 Subsystem 13: Fact Table Loader 121 Subsystem 14: Surrogate Key Pipeline 121 Subsystem 15: Multi-Valued Dimension Bridge Table Builder 121 Subsystem 16: Late-Arriving Data Handler 122 Subsystem 17: Dimension Manager System 122 Subsystem 18: Fact Table Provider System 122 Subsystem 19: Aggregate Builder 123 Subsystem 20: Multidimensional (OLAP) Cube Builder 123 Subsystem 21: Data Integration Manager 123 Managing the ETL Environment 123 Summary 126 Chapter 6 Data Extraction 127 Kettle Data Extraction Overview 128 File-Based Extraction 128 Working with Text Files 128 Working with XML files 133 Special File Types 134 Database-Based Extraction 134 Web-Based Extraction 137 Text-Based Web Extraction 137 HTTP Client 137 Using SOAP 138 Stream-Based and Real-Time Extraction 138 Working with ERP and CRM Systems 138 ERP Challenges 139 Kettle ERP Plugins 140 Working with SAP Data 140 ERP and CDC Issues 146 Data Profiling 146 Using eobjects.org DataCleaner 147 Adding Profile Tasks 149 Adding Database Connections 149 Doing an Initial Profile 151 Working with Regular Expressions 151 Profiling and Exploring Results 152 Validating and Comparing Data 153 Using a Dictionary for Column Dependency Checks 153 Alternative Solutions 154 Text Profiling with Kettle 154 CDC: Change Data Capture 154 Source Data–Based CDC 155 Trigger-Based CDC 157 Snapshot-Based CDC 158 Log-Based CDC 162 Which CDC Alternative Should You Choose? 163 Delivering Data 164 Summary 164 Chapter 7 Cleansing and Conforming 167 Data Cleansing 168 Data-Cleansing Steps 169 Using Reference Tables 172 Conforming Data Using Lookup Tables 172 Conforming Data Using Reference Tables 175 Data Validation 179 Applying Validation Rules 180 Validating Dependency Constraints 183 Error Handling 183 Handling Process Errors 184 Transformation Errors 186 Handling Data (Validation) Errors 187 Auditing Data and Process Quality 191 Deduplicating Data 192 Handling Exact Duplicates 193 The Problem of Non-Exact Duplicates 194 Building Deduplication Transforms 195 Step 1: Fuzzy Match 197 Step 2: Select Suspects 198 Step 3: Lookup Validation Value 198 Step 4: Filter Duplicates 199 Scripting 200 Formula 201 JavaScript 202 User-Defined Java Expressions 202 Regular Expressions 203 Summary 205 Chapter 8 Handling Dimension Tables 207 Managing Keys 208 Managing Business Keys 209 Keys in the Source System 209 Keys in the Data Warehouse 209 Business Keys 209 Storing Business Keys 210 Looking Up Keys with Kettle 210 Generating Surrogate Keys 210 The “Add sequence” Step 211 Working with auto_increment or IDENTITY Columns 217 Keys for Slowly Changing Dimensions 217 Loading Dimension Tables 218 Snowflaked Dimension Tables 218 Top-Down Level-Wise Loading 219 Sakila Snowflake Example 219 Sample Transformation 221 Database Lookup Configuration 222 Sample Job 225 Star Schema Dimension Tables 226 Denormalization 226 Denormalizing to 1NF with the “Database lookup” Step 226 Change Data Capture 227 Slowly Changing Dimensions 228 Types of Slowly Changing Dimensions 228 Type 1 Slowly Changing Dimensions 229 The Insert / Update Step 229 Type 2 Slowly Changing Dimensions 232 The “Dimension lookup / update” Step 232 Other Types of Slowly Changing Dimensions 237 Type 3 Slowly Changing Dimensions 237 Hybrid Slowly Changing Dimensions 238 More Dimensions 239 Generated Dimensions 239 Date and Time Dimensions 239 Generated Mini-Dimensions 239 Junk Dimensions 241 Recursive Hierarchies 242 Summary 243 Chapter 9 Loading Fact Tables 245 Loading in Bulk 246 STDIN and FIFO 247 Kettle Bulk Loaders 248 MySQL Bulk Loading 249 LucidDB Bulk Loader 249 Oracle Bulk Loader 249 PostgreSQL Bulk Loader 250 Table Output Step 250 General Bulk Load Considerations 250 Dimension Lookups 251 Maintaining Referential Integrity 251 The Surrogate Key Pipeline 252 Using In-Memory Lookups 253 Stream Lookups 253 Late-Arriving Data 255 Late-Arriving Facts 256 Late-Arriving Dimensions 256 Fact Table Handling 260 Periodic and Accumulating Snapshots 260 Introducing State-Oriented Fact Tables 261 Loading Periodic Snapshots 263 Loading Accumulating Snapshots 264 Loading State-Oriented Fact Tables 265 Loading Aggregate Tables 266 Summary 267 Chapter 10 Working with OLAP Data 269 OLAP Benefits and Challenges 270 OLAP Storage Types 272 Positioning OLAP 272 Kettle OLAP Options 273 Working with Mondrian 274 Working with XML/A Servers 277 Working with Palo 282 Setting Up the Palo Connection 283 Palo Architecture 284 Reading Palo Data 285 Writing Palo Data 289 Summary 291 Part III Management and Deployment 293 Chapter 11 ETL Development Lifecycle 295 Solution Design 295 Best and Bad Practices 296 Data Mapping 297 Naming and Commentary Conventions 298 Common Pitfalls 299 ETL Flow Design 300 Reusability and Maintainability 300 Agile Development 301 Testing and Debugging 306 Test Activities 307 ETL Testing 308 Test Data Requirements 308 Testing for Completeness 309 Testing Data Transformations 311 Test Automation and Continuous Integration 311 Upgrade Tests 312 Debugging 312 Documenting the Solution 315 Why Isn’t There Any Documentation? 316 Myth 1: My Software Is Self-Explanatory 316 Myth 2: Documentation Is Always Outdated 316 Myth 3: Who Reads Documentation Anyway? 317 Kettle Documentation Features 317 Generating Documentation 319 Summary 320 Chapter 12 Scheduling and Monitoring 321 Scheduling 321 Operating System–Level Scheduling 322 Executing Kettle Jobs and Transformations from the Command Line 322 UNIX-Based Systems: cron 326 Windows: The at utility and the Task Scheduler 327 Using Pentaho’s Built-in Scheduler 327 Creating an Action Sequence to Run Kettle Jobs and Transformations 328 Kettle Transformations in Action Sequences 329 Creating and Maintaining Schedules with the Administration Console 330 Attaching an Action Sequence to a Schedule 333 Monitoring 333 Logging 333 Inspecting the Log 333 Logging Levels 335 Writing Custom Messages to the Log 336 E‑mail Notifications 336 Configuring the Mail Job Entry 337 Summary 340 Chapter 13 Versioning and Migration 341 Version Control Systems 341 File-Based Version Control Systems 342 Organization 342 Leading File-Based VCSs 343 Content Management Systems 344 Kettle Metadata 344 Kettle XML Metadata 345 Transformation XML 345 Job XML 346 Global Replace 347 Kettle Repository Metadata 348 The Kettle Database Repository Type 348 The Kettle File Repository Type 349 The Kettle Enterprise Repository Type 350 Managing Repositories 350 Exporting and Importing Repositories 350 Upgrading Your Repository 351 Version Migration System 352 Managing XML Files 352 Managing Repositories 352 Parameterizing Your Solution 353 Summary 356 Chapter 14 Lineage and Auditing 357 Batch-Level Lineage Extraction 358 Lineage 359 Lineage Information 359 Impact Analysis Information 361 Logging and Operational Metadata 363 Logging Basics 363 Logging Architecture 364 Setting a Maximum Buffer Size 365 Setting a Maximum Log Line Age 365 Log Channels 366 Log Text Capturing in a Job 366 Logging Tables 367 Transformation Logging Tables 367 Job Logging Tables 373 Summary 374 Part IV Performance and Scalability 375 Chapter 15 Performance Tuning 377 Transformation Performance: Finding the Weakest Link 377 Finding Bottlenecks by Simplifying 379 Finding Bottlenecks by Measuring 380 Copying Rows of Data 382 Improving Transformation Performance 384 Improving Performance in Reading Text Files 384 Using Lazy Conversion for Reading Text Files 385 Single-File Parallel Reading 385 Multi-File Parallel Reading 386 Configuring the NIO Block Size 386 Changing Disks and Reading Text Files 386 Improving Performance in Writing Text Files 387 Using Lazy Conversion for Writing Text Files 387 Parallel Files Writing 387 Changing Disks and Writing Text Files 387 Improving Database Performance 388 Avoiding Dynamic SQL 388 Handling Roundtrips 388 Handling Relational Databases 390 Sorting Data 392 Sorting on the Database 393 Sorting in Parallel 393 Reducing CPU Usage 394 Optimizing the Use of JavaScript 394 Launching Multiple Copies of a Step 396 Selecting and Removing Values 397 Managing Thread Priorities 397 Adding Static Data to Rows of Data 397 Limiting the Number of Step Copies 398 Avoiding Excessive Logging 398 Improving Job Performance 399 Loops in Jobs 399 Database Connection Pools 400 Summary 401 Chapter 16 Parallelization, Clustering, and Partitioning 403 Multi-Threading 403 Row Distribution 404 Row Merging 405 Row Redistribution 406 Data Pipelining 407 Consequences of Multi-Threading 408 Database Connections 408 Order of Execution 409 Parallel Execution in a Job 411 Using Carte as a Slave Server 411 The Configuration File 411 Defining Slave Servers 412 Remote Execution 413 Monitoring Slave Servers 413 Carte Security 414 Services 414 Clustering Transformations 417 Defining a Cluster Schema 417 Designing Clustered Transformations 418 Execution and Monitoring 420 Metadata Transformations 421 Rules 422 Data Pipelining 425 Partitioning 425 Defining a Partitioning Schema 425 Objectives of Partitioning 427 Implementing Partitioning 428 Internal Variables 428 Database Partitions 429 Partitioning in a Clustered Transformation 430 Summary 430 Chapter 17 Dynamic Clustering in the Cloud 433 Dynamic Clustering 433 Setting Up a Dynamic Cluster 434 Using the Dynamic Cluster 436 Cloud Computing 437 EC2 438 Getting Started with EC2 438 Costs 438 Customizing an AMI 439 Packaging a New AMI 442 Terminating an AMI 442 Running a Master 442 Running the Slaves 443 Using the EC2 Cluster 444 Monitoring 445 The Lightweight Principle and Persistence Options 446 Summary 447 Chapter 18 Real-Time Data Integration 449 Introduction to Real-Time ETL 449 Real-Time Challenges 450 Requirements 451 Transformation Streaming 452 A Practical Example of Transformation Streaming 454 Debugging 457 Third-Party Software and Real-Time Integration 458 Java Message Service 459 Creating a JMS Connection and Session 459 Consuming Messages 460 Producing Messages 460 Closing Shop 460 Summary 461 Part V Advanced Topics 463 Chapter 19 Data Vault Management 465 Introduction to Data Vault Modeling 466 Do You Need a Data Vault? 466 Data Vault Building Blocks 467 Hubs 467 Links 468 Satellites 469 Data Vault Characteristics 471 Building a Data Vault 471 Transforming Sakila to the Data Vault Model 472 Sakila Hubs 472 Sakila Links 473 Sakila Satellites 474 Loading the Data Vault: A Sample ETL Solution 477 Installing the Sakila Data Vault 477 Setting Up the ETL Solution 477 Creating a Database Account 477 The Sample ETL Data Vault Solution 478 Sample Hub: hub_actor 478 Sample Link: link_customer_store 480 Sample Satellite: sat_actor 483 Loading the Data Vault Tables 485 Updating a Data Mart from a Data Vault 486 The Sample ETL Solution 486 The dim_actor Transformation 486 The dim_customer Transformation 488 The dim_film Transformation 492 The dim_film_actor_bridge Transformation 492 The fact_rental Transformation 493 Loading the Star Schema Tables 495 Summary 495 Chapter 20 Handling Complex Data Formats 497 Non-Relational and Non-Tabular Data Formats 498 Non-Relational Tabular Formats 498 Handling Multi-Valued Attributes 498 Using the Split Field to Rows Step 499 Handling Repeating Groups 500 Using the Row Normaliser Step 500 Semi- and Unstructured Data 501 Kettle Regular Expression Example 503 Configuring the Regex Evaluation Step 504 Verifying the Match 507 Key/Value Pairs 508 Kettle Key/Value Pairs Example 509 Text File Input 509 Regex Evaluation 510 Grouping Lines into Records 511 Denormaliser: Turning Rows into Columns 512 Summary 513 Chapter 21 Web Services 515 Web Pages and Web Services 515 Kettle Web Features 516 General HTTP Steps 516 Simple Object Access Protocol 517 Really Simple Syndication 517 Apache Virtual File System Integration 517 Data Formats 517 XML 518 Kettle Steps for Working with XML 518 Kettle Job Entries for XML 519 HTML 520 JavaScript Object Notation 520 Syntax 521 JSON, Kettle, and ETL/DI 522 XML Examples 523 Example XML Document 523 XML Document Structure 523 Mapping to the Sakila Sample Database 524 Extracting Data from XML 525 Overall Design: The import_xml_into_db Transformation 526 Using the XSD Validator Step 528 Using the “Get Data from XML” Step 530 Generating XML Documents 537 Overall Design: The export_xml_from_db Transformation 537 Generating XML with the Add XML Step 538 Using the XML Join Step 541 SOAP Examples 544 Using the “Web services lookup” Step 544 Configuring the “Web services lookup” Step 544 Accessing SOAP Services Directly 546 JSON Example 549 The Freebase Project 549 Freebase Versus Wikipedia 549 Freebase Web Services 550 The Freebase Read Service 550 The Metaweb Query Language 551 Extracting Freebase Data with Kettle 553 Generate Rows 554 Issuing a Freebase Read Request 555 Processing the Freebase Result Envelope 556 Filtering Out the Original Row 557 Storing to File 558 RSS 558 RSS Structure 558 Channel 558 Item 559 RSS Support in Kettle 560 RSS Input 561 RSS Output 562 Summary 567 Chapter 22 Kettle Integration 569 The Kettle API 569 The LGPL License 569 The Kettle Java API 570 Source Code 570 Building Kettle 571 Building javadoc 571 Libraries and the Class Path 571 Executing Existing Transformations and Jobs 571 Executing a Transformation 572 Executing a Job 573 Embedding Kettle 574 Pentaho Reporting 574 Putting Data into a Transformation 576 Dynamic Transformations 580 Dynamic Template 583 Dynamic Jobs 584 Executing Dynamic ETL in Kettle 586 Result 587 Replacing Metadata 588 Direct Changes with the API 589 Using a Shared Objects File 589 OEM Versions and Forks 590 Creating an OEM Version of PDI 590 Forking Kettle 591 Summary 592 Chapter 23 Extending Kettle 593 Plugin Architecture Overview 593 Plugin Types 594 Architecture 595 Prerequisites 596 Kettle API Documentation 596 Libraries 596 Integrated Development Environment 596 Eclipse Project Setup 597 Examples 598 Transformation Step Plugins 599 StepMetaInterface 599 Value Metadata 605 Row Metadata 606 StepDataInterface 607 StepDialogInterface 607 Eclipse SWT 607 Form Layout 607 Kettle UI Elements 609 Hello World Example Dialog 609 StepInterface 614 Reading Rows from Specific Steps 616 Writing Rows to Specific Steps 616 Writing Rows to Error Handling 617 Identifying a Step Copy 617 Result Feedback 618 Variable Substitution 618 Apache VFS 619 Step Plugin Deployment 619 The User-Defined Java Class Step 620 Passing Metadata 620 Accessing Input and Fields 620 Snippets 620 Example 620 Job Entry Plugins 621 JobEntryInterface 622 JobEntryDialogInterface 624 Partitioning Method Plugins 624 Partitioner 625 Repository Type Plugins 626 Database Type Plugins 627 Summary 628 Appendix A The Kettle Ecosystem 629 Kettle Development and Versions 629 The Pentaho Community Wiki 631 Using the Forums 631 Jira 632 ##pentaho 633 Appendix B Kettle Enterprise Edition Features 635 Appendix C Built-in Variables and Properties Reference 637 Internal Variables 637 Kettle Variables 640 Variables for Configuring VFS 641 Noteworthy JRE Variables 642 Index 643

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Book SynopsisImprove the performance of relational databases with indexes designed for today''s hardwareOver the last few years, hardware and software have advanced beyond all recognition, so it''s hardly surprising that relational database performance now receives much less attention. Unfortunately, the reality is that the improved hardware hasn''t kept pace with the ever-increasing quantity of data processed today. Although disk packing densities have increased enormously, making storage costs extremely low and sequential read very fast, random reads are still painfully slow. Many of the old design recommendations are therefore no longer valid-the optimal point of indexing has come a long way. Consequently many of the old problems haven''t actually gone away-they have simply changed their appearance.This book provides an easy but effective approach to the design of indexes and tables. Using lots of examples and case studies, the authors describe how the DB2, Oracle, and SQTrade Review"I recommend this book to all those who have anything to do with database performance. It is a must-read for all database administrations, database designers, performance-tuning specialists, and application programmers…" (Computing Reviews.com, November 20, 2005)Table of ContentsPreface. 1. Introduction. Another Book About SQL Performance! Inadequate Indexing. Myths and Misconceptions. 2. Table and Index Organization. Introduction. Index Rows. Index Structure. Table Row. Buffer Pools and Disk I/Os. Hardware Specifics. DBMS Specifics. 3. SQL Processing. Introduction. Predicates. Optimizers and Access Paths. Filter Factors. Materializing the Result Rows. Exercises. 4. Deriving the Ideal Index for a SELECT. Introduction. Basic Assumptions for Disk and CPU Times. Inadequate Index. Three-Star Index—The Ideal Index for a SELECT. Algorithm to Derive the Best Index for a SELECT. Ideal Index for Every SELECT? Cost of an Additional Index. Recommendation. Exercises. 5. Proactive Index Design. Detection of Inadequate Indexing. Basic Question (BQ). Quick Upper-Bound Estimate (QUBD). Cheapest Adequate Index or Best Possible Index: Example 1. Cheapest Adequate Index or Best Possible Index: Example 2. When to Use the QUBE. 6. Factors Affecting the Index Design Process. I/O Time Estimate Verification. Multiple Thin Index Slices. Difficult Predicates. Filter Factor Pitfall. Filter Factor Pitfall Example. Exercises. 7. Reactive Index Design. Introduction. EXPLAIN Describes the Selected Access Paths. Monitoring Reveals the Reality. LRT-Level Exception Monitoring. Call-Level Exception Monitoring. DBMS-Specific Monitoring Issues. Exercises. 8. Indexing for Table Joins. Introduction. Two Simple Joins. Impact of Table Access Order on Index Design. Basic Joint Question (BJQ). Predicting the Table Access Order. Merge Scan Joins and Hash Joins. Nested-Loop Joins Versus MS/HJ and Ideal Indexes. Joining More Than Two Tables. Why Joins Often Perform Poorly. Designing Indexes for Subqueries. Designing Indexes for Unions. Table Design Considerations. Exercises. 9. Star Join Considerations. Introduction. Indexes on Dimension tables. Huge Impact of the Table Access Order. Indexes on Fact Tables. Summary Tables. 10. Multiple Index Access. Introduction. Index ANDing. Index ORing. Index Join. Exercises. 11. Indexes and Reorganization. Physical Structure of a B-Tree Index. How the DBMS Finds an Index Row. What Happens When a Row IS Inserted? Are Leaf Page Splits Serious? When Should an Index Be reorganized? Volatile Index Columns. Long Index Rows. Example: Order-Sensitive Batch Job. Table Rows Stored in Leaf Pages. Cost of Index Reorganization. Split Monitoring. Summary. 12. DBMS-Specific Indexing Restrictions. Introduction. Number of Index Columns, Total Length of the Index Columns. Variable-Length Columns. Number of Indexes per Table. Maximum Index Size. Index Locking. Index Row Suppression. DBMS Index Creation Examples. 13. DBMS-Specific Indexing Options. Introduction. Index Row Suppression. Additional Index Columns After the Index Key. Constraints to Enforce Uniqueness. DBMS Able to Read an Index in Both Directions. Index Key Truncation. Function-Based Indexes. Index Skip Scan. Block Indexes. Data-Partitioned Secondary Indexes. Exercises. 14. Optimizers Are Not Perfect. Introduction. Optimizers Do Not Always See the Best Alternative. Optimizers’ Cost Estimates May Be Very Wrong. Cost Estimate Formulas. Do Optimizer Problems Affect Index Design? Exercises. 15. Additional Estimation Considerations. Assumptions Behind the QUBE Formula. Nonleaf Index Pages in Memory. When the Actual Response Time Can Be Much Shorter Than the QUBE. Estimating CPU Time (CQUBE). CPU Estimation Examples. 16. Organizing the Index Design Process. Introduction. Computer-Assisted Index Design. Nine Steps Toward Excellent Indexes. References. Glossary. Index.

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Book SynopsisViews are a key part of database technology, but they're often considered read-only. In this book, Chris Date - a leading expert in relational databases - offers practical techniques that allow you to update the views that a database presents to you.

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Book SynopsisDevelopers, your guide to ABAP for SAP S/4HANA is here. Master the end-to-end development process for SAP S/4HANA applications using the new ABAP programming model. Build applications from scratch, or use SAP Fiori elements to get a head start! Then, deploy your applications to the SAP Fiori launchpad and get the best practices you need to operate applications post-development, including Git version control, application tests, and setting up an integration pipeline. a. Getting Started - Get the development foundation you need and master SAP S/4HANA architecture, SAP Fiori, design-led development strategies, and the new ABAP programming model. b. End-to-End Development - Use step-by-step instructions to develop in SAP S/4HANA using Core Data Services, SAP Gateway, OData, Service Adaptation Description Language, and BOPF. Create list reports and object pages, overview pages, analytical list pages, freestyle applications, and more. c. Operating Applications - Once your applications are deTable of Contents Preface Purpose of This Book Target Audience Structure of This Book Acknowledgments SAP S/4HANA and SAP Fiori SAP S/4HANA Architecture Core Architecture Backend User Experience SAP S/4HANA Editions SAP Cloud Platform Summary SAP Fiori and the Design-Led Development Process What Is SAP Fiori? Design-Led Development Process Different SAP Fiori App Types Prototyping Tools Summary ABAP Programing Model for SAP Fiori Core Data Services SAP Gateway OData Service Adaptation Description Language Business Object Processing Framework SAP Fiori Summary Developing Applications for SAP S/4HANA Developing an SAP Fiori Elements List Report and Object Page Core Data Services Views Transactional Processing with the Business Object Processing Framework Virtual Elements in Core Data Services Creating an OData Service Adding User Interface Annotations Generating a List Report Template in SAP Web IDE Full-Stack Extending the User Interface List Report Application versus Worklist Application Summary Developing an Overview Page Core Data Services Views Adding User Interface Annotations Creating an OData Service Exposing CDS Views as an OData Service Generating an Overview Page Template Project in SAP Web IDE Summary Developing an Analytical List Page Introduction Building the Required CDS Views Configuring the Title Area Configuring the Filter Area Configuring the Content Area Combining All the UI Annotations in the Metadata Extension View Generating an Analytical List Page from SAP Web IDE Summary Developing a Freestyle Application Smart Controls Application Development with the SAP Web IDE Full-Stack Summary Deploying Applications to the SAP Fiori Launchpad Uploading a User Interface to the ABAP Frontend Server SAP Fiori Launchpad Admin Page Creating the Technical Catalog and Business Catalog Creating the Application Tiles Creating Groups for Application Tiles Creating and Assigning a Transaction PFCG Role to Users Setting Up Intent-Based Cross-Application Navigation from OVP to LRP Summary Operating Applications Version Control in SAP Web IDE Using Git Git Introduction Git Basics Summary Automated Testing Backend Test Automation Frontend Test Automation End-to-End Test Automation Tools Summary Continuous Integration Introduction Setting Up a Continuous Integration Pipeline for SAPUI5 on the ABAP Server Continuous Integration on the ABAP Server Summary Appendices Developing Applications on the SAP Cloud Platform The Authors Index

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Book SynopsisA typical Oracle database has multiple users working simultaneously. Data is shared amongst the users, and this of course leads to security concerns. This book comes in from the angle of developing and maintaining a secure Oracle database with multiple users. The book shows how data can be shared in an orderly fashion and what a good secure database is. In this book, we assume that you are acquainted with basic Oracle SQL and fundamentals of relational database.Table of ContentsPreface; Traumatic Stress and Spontaneity: Trauma-Focused and Strengths-Based Psychodrama; Ten Psychodramatic Techniques for Use in Psychoeducational Interventions; Effectiveness of a Psychodramatic Intervention focused on Parent-Adolescent Relationships: The Role of Emotional Attention In Adolescents with Problem Behaviour; Psychodrama. The Model and Contributions of J. G. Rojas-Bermúdez; Therapeutic Mask in Psychodrama with Adolescents; Psychodrama and empowerment in facing violence and death: Social settings beyond psychotherapy; Index.

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