Description

Book Synopsis
Jan-Willem Middelburg is a Dutch entrepreneur and author with a passion for technology and innovation. He is the CEO and co-founder of Cybiant, a global technology that company that helps to create a more sustainable world through analytics, big data and automation. He is also President and Chief Examiner of the Enterprise Big Data Framework, an independent organization dedicated to upskilling individuals with expertise in Big Data. In partnership with APMG-International, the Enterprise Big Data Framework offers vendor-neutral certifications for individuals.

Trade Review
"The Enterprise Big Data Framework is relevant for everybody within an organisation engaged in driving maximum benefits from data. There is something for everybody; from the board considering governance and ethical behaviour to individuals within the organisation knowing where they fit and the value they can get from better use of their organisation's data. If you are considering a transformation project, this is an excellent guide for your project team." * Richard Pharro, CEO, The APM Group Limited *
"If you are looking for a good guide to empower your knowledge on big data and to find a framework to help you on your big data journey, then this book is for you. From learning what big data is to defining a big data strategy, Jan-Willem has built a book to empower the learner on the topic of big data." * Jordan Morrow, Chief Strategy & Transformation Officer, DataPrime and Author of Be Data Literate *
"This book is a master piece for those who are familiar and those who discover the world of data. It provides an "a la carte framework" starting with a (big) data strategy and the supporting aspects such as big data functions, architecture and algorithms. It covers in depth data platforms architectures, its management as well as data governance, data catalogue and all the required security considerations associated to the various data classifications. You will find details of data life cycle management, of various machine learning algorithms and an important chapter covering AI ethics when building and deploying sophisticated algorithms using data. The concepts covered in this book apply to on-premises and in the (public) cloud environments, making this book a must read." * Jean-Michel Coeur, APAC Technology Practice Lead, Data Analytics, Google Cloud *

Table of Contents
  • Section - ONE: Introduction to Big Data;
    • Chapter - 01: Introduction to Big Data;
    • Chapter - 02: The Big Data framework;
    • Chapter - 03: Big Data strategy;
    • Chapter - 04: Big Data architecture;
    • Chapter - 05: Big Data algorithms;
    • Chapter - 06: Big Data processes;
    • Chapter - 07: Big Data functions;
    • Chapter - 08: Artificial intelligence;
  • Section - TWO: Enterprise Big Data analysis;
    • Chapter - 09: Introduction to Big Data analysis;
    • Chapter - 10: Defining the business objective;
    • Chapter - 11: Data ingestion – importing and reading data sets;
    • Chapter - 12: Data preparation – cleaning and wrangling data;
    • Chapter - 13: Data analysis – model building;
    • Chapter - 14: Data presentation;
  • Section - THREE: Enterprise Big Data engineering;
    • Chapter - 15: Introduction to Big Data engineering;
    • Chapter - 16: Data modelling;
    • Chapter - 17: Constructing the data lake;
    • Chapter - 18: Building an enterprise Big Data warehouse;
    • Chapter - 19: Design and structure of Big Data pipelines;
    • Chapter - 20: Managing data pipelines;
    • Chapter - 21: Cluster technology;
  • Section - FOUR: enterprise Big Data algorithm design;
    • Chapter - 22: Introduction to Big Data algorithm design;
    • Chapter - 23: Algorithm design – fundamental concepts;
    • Chapter - 24: Statistical machine learning algorithms;
    • Chapter - 25: The data science roadmap;
    • Chapter - 26: Programming languages 26 visualization and simple metrics;
    • Chapter - 27: Advanced machine learning algorithms;
    • Chapter - 28: Advanced machine learning classification algorithms;
    • Chapter - 29: Technical communication and documentation;
  • Section - FIVE: Enterprise Big Data architecture;
    • Chapter - 30: Introduction to the Big Data architecture;
    • Chapter - 31: Strength and resilience – the Big Data platform;
    • Chapter - 32: Design principles for Big Data architecture;
    • Chapter - 33: Big Data infrastructure;
    • Chapter - 34: Big Data platforms;
    • Chapter - 35: The Big Data application provider;
    • Chapter - 36: System orchestration in Big Data

The Enterprise Big Data Framework

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A Hardback by Jan-Willem Middelburg

15 in stock


    View other formats and editions of The Enterprise Big Data Framework by Jan-Willem Middelburg

    Publisher: Kogan Page Ltd
    Publication Date: 03/11/2023
    ISBN13: 9781398601741, 978-1398601741
    ISBN10: 1398601748
    Also in:
    Algorithms and data structures Data warehousing Data science and analysis

    Description

    Book Synopsis
    Jan-Willem Middelburg is a Dutch entrepreneur and author with a passion for technology and innovation. He is the CEO and co-founder of Cybiant, a global technology that company that helps to create a more sustainable world through analytics, big data and automation. He is also President and Chief Examiner of the Enterprise Big Data Framework, an independent organization dedicated to upskilling individuals with expertise in Big Data. In partnership with APMG-International, the Enterprise Big Data Framework offers vendor-neutral certifications for individuals.

    Trade Review
    "The Enterprise Big Data Framework is relevant for everybody within an organisation engaged in driving maximum benefits from data. There is something for everybody; from the board considering governance and ethical behaviour to individuals within the organisation knowing where they fit and the value they can get from better use of their organisation's data. If you are considering a transformation project, this is an excellent guide for your project team." * Richard Pharro, CEO, The APM Group Limited *
    "If you are looking for a good guide to empower your knowledge on big data and to find a framework to help you on your big data journey, then this book is for you. From learning what big data is to defining a big data strategy, Jan-Willem has built a book to empower the learner on the topic of big data." * Jordan Morrow, Chief Strategy & Transformation Officer, DataPrime and Author of Be Data Literate *
    "This book is a master piece for those who are familiar and those who discover the world of data. It provides an "a la carte framework" starting with a (big) data strategy and the supporting aspects such as big data functions, architecture and algorithms. It covers in depth data platforms architectures, its management as well as data governance, data catalogue and all the required security considerations associated to the various data classifications. You will find details of data life cycle management, of various machine learning algorithms and an important chapter covering AI ethics when building and deploying sophisticated algorithms using data. The concepts covered in this book apply to on-premises and in the (public) cloud environments, making this book a must read." * Jean-Michel Coeur, APAC Technology Practice Lead, Data Analytics, Google Cloud *

    Table of Contents
    • Section - ONE: Introduction to Big Data;
      • Chapter - 01: Introduction to Big Data;
      • Chapter - 02: The Big Data framework;
      • Chapter - 03: Big Data strategy;
      • Chapter - 04: Big Data architecture;
      • Chapter - 05: Big Data algorithms;
      • Chapter - 06: Big Data processes;
      • Chapter - 07: Big Data functions;
      • Chapter - 08: Artificial intelligence;
    • Section - TWO: Enterprise Big Data analysis;
      • Chapter - 09: Introduction to Big Data analysis;
      • Chapter - 10: Defining the business objective;
      • Chapter - 11: Data ingestion – importing and reading data sets;
      • Chapter - 12: Data preparation – cleaning and wrangling data;
      • Chapter - 13: Data analysis – model building;
      • Chapter - 14: Data presentation;
    • Section - THREE: Enterprise Big Data engineering;
      • Chapter - 15: Introduction to Big Data engineering;
      • Chapter - 16: Data modelling;
      • Chapter - 17: Constructing the data lake;
      • Chapter - 18: Building an enterprise Big Data warehouse;
      • Chapter - 19: Design and structure of Big Data pipelines;
      • Chapter - 20: Managing data pipelines;
      • Chapter - 21: Cluster technology;
    • Section - FOUR: enterprise Big Data algorithm design;
      • Chapter - 22: Introduction to Big Data algorithm design;
      • Chapter - 23: Algorithm design – fundamental concepts;
      • Chapter - 24: Statistical machine learning algorithms;
      • Chapter - 25: The data science roadmap;
      • Chapter - 26: Programming languages 26 visualization and simple metrics;
      • Chapter - 27: Advanced machine learning algorithms;
      • Chapter - 28: Advanced machine learning classification algorithms;
      • Chapter - 29: Technical communication and documentation;
    • Section - FIVE: Enterprise Big Data architecture;
      • Chapter - 30: Introduction to the Big Data architecture;
      • Chapter - 31: Strength and resilience – the Big Data platform;
      • Chapter - 32: Design principles for Big Data architecture;
      • Chapter - 33: Big Data infrastructure;
      • Chapter - 34: Big Data platforms;
      • Chapter - 35: The Big Data application provider;
      • Chapter - 36: System orchestration in Big Data

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