AUMELBAS281

Big Data Fundamentals: Concepts, Drivers & Techniques eBook

Thomas Erl
...show all

Big Data Fundamentals: Concepts, Drivers & Techniques eBook

By Thomas Erl, Wajid Khattak, Paul Buhler
$38.95
In stock
Add to cart
Overview
Author
Thomas Erl
...show all
Edition
1st
ISBN
9780134291208
Published Date
30/12/2015

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.

The full text downloaded to your computer

With eBooks you can:

  • search for key concepts, words and phrases
  • make highlights and notes as you study
  • share your notes with friends

eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps.

Upon purchase, you'll gain instant access to this eBook.

Time limit

The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.

Biography
Thomas Erl is a top-selling IT author, founder of Arcitura Education and series editor of the Prentice Hall Service Technology Series from Thomas Erl. With more than 200,000 copies in print worldwide, his books have become international bestsellers and have been formally endorsed by senior members of major IT organizations, such as IBM, Microsoft, Oracle, Intel, Accenture, IEEE, HL7, MITRE, SAP, CISCO, HP and many others. As CEO of Arcitura Education Inc., Thomas has led the development of curricula for the internationally recognized Big Data Science Certified Professional (BDSCP), Cloud Certified Professional (CCP) and SOA Certified Professional (SOACP) accreditation programs, which have established a series of formal, vendor-neutral industry certifications obtained by thousands of IT professionals around the world. Thomas has toured more than 20 countries as a speaker and instructor. More than 100 articles and interviews by Thomas have been published in numerous publications, including The Wall Street Journal and CIO Magazine.

Wajid Khattak is a Big Data researcher and trainer at Arcitura Education Inc. His areas of interest include Big Data engineering and architecture, data science, machine learning, analytics and SOA. He has extensive .NET software development experience in the domains of business intelligence reporting solutions and GIS.

Wajid completed his MSc in Software Engineering and Security with distinction from Birmingham City University in 2008. Prior to that, in 2003, he earned his BSc (Hons) degree in Software Engineering from Birmingham City University with first-class recognition. He holds MCAD & MCTS (Microsoft), SOA Architect, Big Data Scientist, Big Data Engineer and Big Data Consultant (Arcitura) certifications.

Dr. Paul Buhler is a seasoned professional who has worked in commercial, government and academic environments. He is a respected researcher, practitioner and educator of service-oriented computing concepts, technologies and implementation methodologies. His work in XaaS naturally extends to cloud, Big Data and IoE areas. Dr. Buhler’s more recent work has been focused on closing the gap between business strategy and process execution by leveraging responsive design principles and goal-based execution.

As Chief Scientist at Modus21, Dr. Buhler is responsible for aligning corporate strategy with emerging trends in business architecture and process execution frameworks. He also holds an Affiliate Professorship at the College of Charleston, where he teaches both graduate and undergraduate computer science courses. Dr. Buhler earned his Ph.D. in Computer Engineering at the University of South Carolina. He also holds an MS degree in Computer Science from Johns Hopkins University and a BS in Computer Science from The Citadel.
Table of contents
  • Acknowledgments
  • Reader Services    
  • PART I: THE FUNDAMENTALS OF BIG DATA
  • Chapter 1: Understanding Big Data   
  • Chapter 2: Business Motivations and Drivers for Big Data Adoption    
  • Chapter 3: Big Data Adoption and Planning Considerations    
  • Chapter 4: Enterprise Technologies and Big Data Business Intelligence    
  • PART II: STORING AND ANALYZING BIG DATA
  • Chapter 5: Big Data Storage Concepts    
  • Chapter 6: Big Data Processing Concepts    
  • Chapter 7: Big Data Storage Technology    
  • Chapter 8: Big Data Analysis Techniques    
  • Appendix A: Case Study Conclusion    
  • About the Authors    
  • Index