Transform Big Data into Insight
"In this book, some of Oracle's best engineers and architects explain how you can make use of big data. They'll tell you how you can integrate your existing Oracle solutions with big data systems, using each where appropriate and moving data between them as needed." -- Doug Cutting, co-creator of Apache Hadoop
Cowritten by members of Oracle's big data team, Oracle Big Data Handbook provides complete coverage of Oracle's comprehensive, integrated set of products for acquiring, organizing, analyzing, and leveraging unstructured data. The book discusses the strategies and technologies essential for a successful big data implementation, including Apache Hadoop, Oracle Big Data Appliance, Oracle Big Data Connectors, Oracle NoSQL Database, Oracle Endeca, Oracle Advanced Analytics, and Oracle's open source R offerings. Best practices for migrating from legacy systems and integrating existing data warehousing and analytics solutions into an enterprise big data infrastructure are also included in this Oracle Press guide.
|About the authors|
Tom Plunkett is a Senior Sales Consultant with Oracle. Tom also teaches graduate-level computer science courses for Virginia Tech as an adjunct instructor and distance learning instructor. Tom helped win several industry awards for a big data project that Oracle and the Frederick National Laboratory for Cancer Research collaborated on to analyze relationships between genomes and cancer subtypes, including the 2012 Government Big Data Solution Award, ACT-IAC finalist for best pilot/start-up project, and was nominated for a 2013 Computer World Honor Award for Innovation. Tom has spoken internationally at over 40 conferences on the subject of Big Data since leading a team that won a Big Data project from the Office of the Secretary of Defense in 2009. Tom is the lead author of several books, including Oracle Big Data Handbook and Oracle Exalogic Elastic Cloud Handbook. Previously, Tom worked for IBM and practiced patent law for Fliesler Meyer. Tom has a BA and a JD from George Mason University, and an MS in computer science from Virginia Tech.
Brian Macdonald is a Distinguished Solution Consultant and certified Oracle Enterprise Architect with Oracle. He has more than 20 years of experience creating architectures and implementing analytic platforms to address a wide range of customer needs including data warehousing, business intelligence, OLAP, Hadoop, Master Data Management, and ETL technologies.
Bruce Nelson is the Oracle Big Data lead for the Western U.S. and has more than 24 years of experience in the IT industry with a focus on Hadoop, noSQL, Oracle Database, Oracle RAC, and Oracle Exadata.
Mark Hornick is a Director in the Oracle Database Advanced Analytics group focusing on Oracle R Enterprise (ORE), Oracle R Connector for Hadoop (ORCH), and Oracle R Distribution (ORD). He also works with internal and external customers in the application of R for scalable applications in Oracle Database, Exadata, and the Big Data Appliance, also engaging in SAS-to-R conversion and performance benchmarking. Mark is co-author of Java Data Mining: Strategy, Standard, and Practice. He joined Oracle’s Data Mining Technologies group in 1999 through the acquisition of Thinking Machines Corp. Mark was a founding member of and currently serves as an Oracle Advisor to the IOUG Business Intelligence Warehousing and Analytics (BIWA) SIG. He has conducted training sessions on R, ORE, and ORCH in the US, EMEA, APAC, and has presented at conference, including Oracle OpenWorld, Collaborate, BIWA Summit, and the R user conference useR! Mark holds a bachelor’s degree from Rutgers University and a master’s degree from Brown University, both in computer science.
|Table of contents|
1 How to Use This Book
Section I: Introduction
1. Introduction to Big Data
2. Big Data Use Cases
3. Big Data, Concepts, Insights and Operational information
Section II: Big Data Platform
4. The BigData platform BDA, Exadata, Exalytics, Endeca
5. Why an Appliance
6. Configuration options
Section III: Acquiring and Organizing Data
7. Map Reduce Theory and Programming
8. BDA Connectors
9. Oracle noSQL
Section IV: Analyzing Information and Making Decisions
10. In-Database Analytics Minig. OLAP
11. Analyzing Data with R
12. Discovery with Endeca