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The Enterprise Big Data Framework
Building Critical Capabilities to Win in the Data Economy
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About the book
Businesses who can make sense of the huge influx and complexity of data will be the big winners in the information economy.
This comprehensive guide covers all the aspects of transforming enterprise data into value, from the initial set-up of a big data strategy, towards algorithms, architecture and data governance processes. Using a vendor-independent approach, The Enterprise Big Data Framework offers practical advice on how to develop data-driven decision making, detailed data analysis and data engineering techniques.
With a focus on practical implementation, The Enterprise Big Data Framework introduces six critical capabilities that every organization can use to become data driven. With sections on strategy formulation, data governance, sustainability, architecture and algorithms, this guide provides a comprehensive overview of best practices organizations can leverage to win in the data economy. Throughout the different sections, the book also introduces a capability model that every organization can use to measure progress. Endorsed by leading accreditation and examination institute AMPG International, this book is required reading for the Enterprise Big Data Certifications, which aim to develop excellence in big data practices across the globe. Online resources include sample data for practice purposes.
About the authors
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
Reviews
- 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
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