Free Downloads
Big Data Concepts, Theories, And Applications

This book covers three major parts of Big Data: concepts, theories and applications. Written by world-renowned leaders in Big Data, this book explores the problems, possible solutions and directions for Big Data in research and practice.  It also focuses on high level concepts such as definitions of Big Data from different angles; surveys in research and applications; and existing tools, mechanisms, and systems in practice. Each chapter is independent from the other chapters, allowing users to read any chapter directly. After examining the practical side of Big Data, this book presents theoretical perspectives. The theoretical research ranges from Big Data representation, modeling and topology to distribution and dimension reducing.  Chapters also investigate the many disciplines that involve Big Data, such as statistics, data mining, machine learning, networking, algorithms, security and differential geometry. The last section of this book introduces Big Data applications from different communities, such as business, engineering and science. Big Data Concepts, Theories and Applications is designed as a reference for researchers and advanced level students in computer science, electrical engineering and mathematics. Practitioners who focus on information systems, big data, data mining, business analysis and other related fields will also find this material valuable. 

Hardcover: 437 pages

Publisher: Springer; 1st ed. 2016 edition (March 3, 2016)

Language: English

ISBN-10: 3319277618

ISBN-13: 978-3319277615

Product Dimensions: 6.1 x 1 x 9.2 inches

Shipping Weight: 1.8 pounds (View shipping rates and policies)

Average Customer Review: Be the first to review this item

Best Sellers Rank: #1,843,437 in Books (See Top 100 in Books) #368 in Books > Computers & Technology > Hardware & DIY > Internet & Networking #1419 in Books > Computers & Technology > Networking & Cloud Computing > Network Security #3987 in Books > Computers & Technology > Security & Encryption

Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault Big Data For Beginners: Understanding SMART Big Data, Data Mining & Data Analytics For improved Business Performance, Life Decisions & More! Big Data Concepts, Theories, and Applications Data Analytics: Practical Data Analysis and Statistical Guide to Transform and Evolve Any Business Leveraging the Power of Data Analytics, Data Science, ... (Hacking Freedom and Data Driven Book 2) The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences Big Data, MapReduce, Hadoop, and Spark with Python: Master Big Data Analytics and Data Wrangling with MapReduce Fundamentals using Hadoop, Spark, and Python Crain, Theories of DevelopmentConcepts and Applications (Subscription): Concepts and Applications Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection (Data-Centric Systems and Applications) Understanding Cloud, IoT and Big data (Cloud, IoT & Big Data: Basic To AWS SA Professional Book 1) Discovering Knowledge in Data: An Introduction to Data Mining (Wiley Series on Methods and Applications in Data Mining) Intermediate Algebra: Concepts & Applications (Bittinger Concepts & Applications) Theories of Development: Concepts and Applications (5th Edition) (MySearchLab Series) Philosophies And Theories For Advanced Nursing Practice (Butts, Philosophies and Theories for Advanced Nursing Practice) Nursing Theories and Nursing Practice ( Third Edition ) (Parker, Nursing Theories and Nursing Practice) Theories for Direct Social Work Practice (SW 390N 2-Theories of Social Work Practice) Theories of Personality (PSY 235 Theories of Personality) LEARN IN A DAY! DATA WAREHOUSING. Top Links and Resources for Learning Data Warehousing ONLINE and OFFLINE: Use these FREE and PAID resources to Learn Data Warehousing in little to no time Data Just Right: Introduction to Large-Scale Data & Analytics (Addison-Wesley Data and Analytics) Big Data Fundamentals: Concepts, Drivers & Techniques (The Prentice Hall Service Technology Series from Thomas Erl) Introducing Data Science: Big Data, Machine Learning, and more, using Python tools