Big Data Science Fundamentals offers a comprehensive, easy-to-understand, and up-to-date understanding of Big Data for all business professionals and technologists. Leading enterprise technology author Thomas Erl introduces key Big Data concepts, theory, terminology, technologies, key analysis/analytics techniques, and more - all logically organized, presented in plain English, and supported by easy-to-understand diagrams and case study examples. Erl provides a uniquely valuable methodology for Big Data analysis, and introduces the underlying analysis techniques and enabling technological constructs that constitute a Big Data solution environment. He presents vendor-neutral guidance on implementing Big Data for competitive advantage; and for successfully integrating Big Data with existing enterprise systems.
Coverage includes: *Big Data's fundamental concepts and key business/technology drivers*"5 V" characteristics of data in Big Data environments: volume, velocity, variety, veracity, and value*Types of Big Data: structured, unstructured, semi-structured, and meta-data*Big Data's relationships with OLTP, OLAP, ETL, data warehouses, and data marts*Fundamental types of analysis, analytics, and machine learning*Requirements and tools for visualizing big data*Adoption and planning: business cases, privacy, security, provenance, performance, governance, and more*Big Data technologies, including clusters, NoSQL, distributed and parallel data processing, Hadoop, cloud computing, and storage*Big Data analysis and analytics across the full lifecycle*And much more
