Big Data

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The Abstracts

Developing Enterprise Policy Over Big Data
Jim McGann

Bigger is not better when it comes to data--better is. Discover how unstructured data profiling technology allows the enterprise to harness, classify and determine the disposition of data to reclaim storage capacity, reduce budget and mitigate risk.

Learning Objectives

  • Understand why your data center is growing so rapidly and how IT budgets are being compromised 
  • Uncover the makeup of your servers and locate any ROT (redundant, outdated and trivial data) including personal multimedia files, data owned by ex-employees and emails not accessed in over seven years. 
  • Start the conversation between departments to set retention or information governance policies. These may include archiving, tiering or a defensible disposition. 

Introduction to Hadoop and MapReduce
Serge Bazhievsky


Learning Objectives

  • Big data overview
  • Map reduce abstraction

Protecting Data in the Big Data World
Thomas Rivera

Data growth is in an explosive state, and these "Big Data" repositories need to be protected. In addition, new regulations are mandating longer data retention, and the job of protecting these ever-growing data repositories is becoming even more daunting. This presentation will outline the challenges and the methods that can be used for protecting "Big Data" repositories.

Learning Objectives

  • Participants will get to understand the unique challenges of managing and protecting "Big Data" repositories.
  • Participants will be able to understand the various technologies available for protecting "Big Data" repositories.
  • Participants will get to understand the various data protection considerations for "Big Data" repositories, for various environments, including Disaster Recovery/Replication, Capacity Optimization, etc.

Industry's Urgent Need for College-level Data Storage Curriculum
Ramin Elahi

Abstract pending