Jan-Willem Middelburg

The Enterprise Big Data Framework (eBook, ePUB)

Building Critical Capabilities to Win in the Data Economy

• Format: ePub

Produktbeschreibung

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.

Produktdetails

• Verlag: Kogan Page
• Seitenzahl: 496
• Erscheinungstermin: 3. November 2023
• Englisch
• ISBN-13: 9781398601727
• Artikelnr.: 69256737

Autorenporträt

Jan-Willem Middelburg

Inhaltsangabe

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