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
“...one 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.
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algorithm amounts of data analytic results application backend storage batch Big Data analytics Big Data datasets Big Data processing Big Data solution business processes cluster columnfamily consistency dashboard data analysis Data analytics lifecycle data marts data mining data sources data storage data visualization data warehouse distributed file system document enterprise entities ETI’s example execution external data Extract Transform Load extracted filtering fraudulent claims Hadoop ice cream IMDB IMDG implemented inmemory storage device input JSON keyvalue pairs KPIs latency layer leverage machine learning MapReduce masterslave metadata multiple nodes NoSQL database NoSQL storage devices OLAP OLTP ondisk storage device operations output partition performance predictive analytics prescriptive analytics query reduce task relational database replication scalable schema sharding shown in Figure social media stage stored strategic structured Text analytics transaction types unstructured data update variable workloads