Big Data Fundamentals : Concepts, Drivers & Techniques

Big Data Fundamentals : Concepts, Drivers & Techniques


"This text should be required reading for everyone in contemporary business."
--Peter Woodhull, CEO, Modus21

"The one book that clearly describes and links Big Data concepts to business utility."
--Dr. Christopher Starr, PhD

"Simply, this is the best Big Data book on the market!"
--Sam Rostam, Cascadian IT Group

" of the most contemporary approaches I've seen to Big Data fundamentals..."
--Joshua M. Davis, PhD

The Definitive Plain-English Guide to Big Data for Business and Technology Professionals

Big Data Fundamentals provides a pragmatic, no-nonsense introduction to Big Data. Best-selling IT author Thomas Erl and his team clearly explain key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. All coverage is supported with case study examples and numerous simple diagrams.

The authors begin by explaining how Big Data can propel an organization forward by solving a spectrum of previously intractable business problems. Next, they demystify key analysis techniques and technologies and show how a Big Data solution environment can be built and integrated to offer competitive advantages.

Discovering Big Data's fundamental concepts and what makes it different from previous forms of data analysis and data science
Understanding the business motivations and drivers behind Big Data adoption, from operational improvements through innovation
Planning strategic, business-driven Big Data initiatives
Addressing considerations such as data management, governance, and security
Recognizing the 5 "V" characteristics of datasets in Big Data environments: volume, velocity, variety, veracity, and value
Clarifying Big Data's relationships with OLTP, OLAP, ETL, data warehouses, and data marts
Working with Big Data in structured, unstructured, semi-structured, and metadata formats
Increasing value by integrating Big Data resources with corporate performance monitoring
Understanding how Big Data leverages distributed and parallel processing
Using NoSQL and other technologies to meet Big Data's distinct data processing requirements
Leveraging statistical approaches of quantitative and qualitative analysis
Applying computational analysis methods, including machine learning

Similar Books

ISBN 10: 1118965833
ISBN 13: 9781118965832

02 Mar 2015
Bernard Marr

ISBN 10: 1119002257
ISBN 13: 9781119002253

01 Dec 2015
Cole Nussbaumer Knaflic

ISBN 10: 1491912219
ISBN 13: 9781491912218

01 Apr 2018
Bill Chambers

ISBN 10: 1491963042
ISBN 13: 9781491963043

01 Aug 2018
Benjamin Bengfort

ISBN 10: 1449373321
ISBN 13: 9781449373320

02 Apr 2017
Martin Kleppmann

ISBN 10: 0134692888
ISBN 13: 9780134692883

07 Jul 2017
Zed Shaw

ISBN 10: 1119181119
ISBN 13: 9781119181118

02 Feb 2016
Bill Schmarzo

ISBN 10: 0134049942
ISBN 13: 9780134049946

05 Nov 2015
Douglas Eadline

ISBN 10: 1840787953
ISBN 13: 9781840787955

13 Mar 2018
Mike McGrath

ISBN 10: 1491901632
ISBN 13: 9781491901632

01 Apr 2016
Tom White

ISBN 10: 0804136718
ISBN 13: 9780804136716

16 Nov 2016
Philip E. Tetlock

ISBN 10: 0997847913
ISBN 13: 9780997847918

19 Jul 2016
Kenneth C Lichtendahl Jr