內容簡介top Big Data Fundamentals 簡介 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 valueTypes of Big Data: structured, unstructured, semi-structured, and meta-dataBig Data's relationships with OLTP, OLAP, ETL, data warehouses, and data martsFundamental types of analysis, analytics, and machine learningRequirements and tools for visualizing big dataAdoption and planning: business cases, privacy, security, provenance, performance, governance, and moreBig Data technologies, including clusters, NoSQL, distributed and parallel data processing, Hadoop, cloud computing, and storageBig Data analysis and analytics across the full lifecycleAnd much more