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Market Research Report

BI on Hadoop, Part 1

Published by Ovum (TMT Intelligence, Informa) Product code 288848
Published Content info 17 Pages
Delivery time: 1-2 business days
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BI on Hadoop, Part 1
Published: October 10, 2013 Content info: 17 Pages
Description

Until recently, Big Data analytics have typically been associated with advanced programmatic-style analytic techniques on emerging NoSQL platforms, or complex, data mining-oriented runs against large enterprise SQL data warehouses. That triggers an obvious question -- could Hadoop become more accessible with the BI tools that have become a staple of analytics for many enterprises?

Highlights

  • Hadoop will augment, not replace, the traditional enterprise data warehouse.
  • SQL is rapidly becoming a preferred way for BI users to access Hadoop.
  • Data discovery and search tools become increasingly important as more data enters the BI process.

Features Benefits

  • Outlines new use cases for adding Hadoop to the BI stack.
  • Discusses the opportunities and limitations of BI with Hadoop today and going forward.
  • Discusses the types of interaction that different BI roles (casual user, power user, BI developer, BI administrator, etc) will have with Hadoop.

Questions Answers

  • When and why should Hadoop be considered for BI processes?
  • How can Hadoop augment BI implementations?
Table of Contents
Product Code: IT014-002804

Table of Contents

Headings

  • SUMMARY
    • Catalyst
    • Ovum view
    • Key messages
    • Overview of report series
  • THE STATE OF BI TODAY
    • Ovum's definition of business intelligence
    • BI and SQL
      • A mature market
      • The appeal of SQL
      • The limitations of SQL
    • Hadoop
      • Why are we having this conversation?
      • Hadoop's limitations
      • Changes are on the horizon
  • HADOOP ADDS BUSINESS VALUE TO BI PROCESSES
    • Hadoop is not replacing EDWs...
    • ...but Hadoop can go where EDWs cannot
      • Keeping it raw
      • Hadoop-augmented BI stack - adding new types of data sources to the BI lifecycle
      • Active archiving
  • HOW DOES HADOOP CHANGE THE BI THOUGHT PROCESS?
    • Bigger ways of answering familiar questions
    • BI tools and techniques to help frame these questions
      • Data discovery and search can be a first analytic step
      • Search will help users find the data they are looking for
      • Graph processing to better understand what is connected to what
    • Who can benefit from BI on Hadoop?
      • Casual end user
      • Power user/data curator
      • Developer
      • Administrator
  • RECOMMENDATIONS
    • Recommendations for enterprises
      • Hadoop is still a young technology - know-how might need to be acquired
      • Start small and scale out
      • Don't add data "just because"
    • Recommendations for vendors
      • Guidance and education will be key
      • Expand Big Data know-how internally
      • Improve Big Data-related professional services externally
      • Don't run away from core BI customers
  • APPENDIX
    • Methodology
    • Further reading
    • Author
    • Ovum Consulting
    • Disclaimer
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