The Enterprise Big Data Framework

Edition: 1 Date: 03/09/2022 Price: £49.99 ISBN Paperback: 9781398601710 ISBN Ebook: 9781398601727 Pages: 568 Format (mm): 240x170 Product Category: Supplementary Text/

Professional

Subject: Information, Knowledge

& Data Management

«Focuses on the enterprise implementation of the big data framework, covering analysis, engineering, algorithm design and architecture « Offers a vendor-independent approach to transforming massive quantities of data into value « Covers detailed data analysis and data engineering techniques for anyone who wants a deep understanding of big data « Helps readers understand the core concepts and techniques that underpin the somewhat abstract concept of big data « Online resources: sample data for practice purposes

Description

Businesses who can make sense of the huge influx and complexity of data will be the big winners in the information economy. Learning how to fully leverage, analyze and integrate big data can help companies reduce costs, increase operating margins and add income.

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 business implementation, The Enterprise Big Data Framework includes sections on analysis, engineering, algorithm design and big data architecture, and covers topics such as data preparation and presentation, data modelling, data science, programming languages and machine learning algorithms. 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.

Author Information

Jan-Willem Middelburg is the CEO and cofounder of Cybiant, based in Kuala Lumpur, Malaysia. With Cybiant he helps to create a more sustainable world through analytics, big data and automation, developing algorithms and employing data scientists to unearth patterns and information. 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.

Table of Contents

1 Introduction to Big Data

1 Introduction to Big Data 2 The Big Data framework 3 Big Data strategy 4 Big Data architecture 5 Big Data algorithms 6 Big Data processes 7 Big Data functions 8 Artificial intelligence

2 Enterprise Big Data analysis

9 Introduction to Big Data analysis 10 Defining the business objective 11 Data ingestion – importing and reading data sets 12 Data preparation – cleaning and wrangling data 13 Data analysis – model building 14 Data presentation

3 Enterprise Big Data engineering

15 Introduction to Big Data engineering 16 Data modelling 17 Constructing the data lake 18 Building an enterprise Big

Data warehouse 19 Design and structure of Big

Data pipelines 20 Managing data pipelines 21 Cluster technology

4 enterprise Big Data algorithm design

22 Introduction to Big Data algorithm design 23 Algorithm design – fundamental concepts 24 Statistical machine learning algorithms 25 The data science roadmap 26 Programming languages 26 visualization and simple metrics 27 Advanced machine learning algorithms 28 Advanced machine learning classification algorithms 29 Technical communication and documentation

5 Enterprise Big Data architecture

30 Introduction to the Big Data architecture 31 Strength and resilience – the

Big Data platform 32 Design principles for Big Data architecture 33 Big Data infrastructure 34 Big Data platforms 35 The Big Data application provider 36 System orchestration in Big

Data