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An introduction to today’s advanced data analytics technology options

Get an overview of advanced data analytics software, including a discussion of the potential uses of analytic technology and advice on creating an advanced analytics strategy.

Advanced data analytics software that can be used to mine data and do what-if analysis has the potential to help organizations gain a competitive advantage over their rivals. But analytic technology, such as data mining tools and predictive analytics applications, has traditionally been the expensive domain of statisticians and other highly skilled workers. And the advanced analytics market can be a challenge for even experienced business and IT professionals to navigate.

In this podcast, Forrester Research Inc. analyst James Kobielus provides an in-depth introduction to advanced analytics technology and concepts, including an overview of what advanced analytics is and what companies can do with data analytics tools. He also discusses the costs of advanced analytics and offers tips and advice on creating or expanding an advanced data analytics strategy.

Listeners will:

  • Get an introduction to advanced analytics, including a discussion of the different types of data analytics software and the potential uses of analytics tools (1:01)
  • Find out whether companies need to hire skilled quantitative analysts, statisticians and mathematicians to take advantage of advanced analytics applications (2:54)
  • Hear about the increased bundling of advanced data analytics software into business intelligence applications, and whether that’s a good thing for users (6:00)
  • Get advice on how to get started with advanced analytics and on expanding the use of analytics tools, including questions to ask internally and common missteps to avoid (7:32)
  • Learn about in-database analytics and the MapReduce and Hadoop technologies, and why they could provide increased flexibility for users of advanced analytics software (12:24)

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James Kobielus

About the speaker: James Kobielus is a senior analyst at Forrester Research Inc., with a focus on data warehousing, predictive analytics, data mining and complex event processing. In addition to those core coverage areas, he contributes to Forrester’s research on business intelligence, data integration, data quality and master data management. Kobielus worked previously for other IT research firms and several technology vendors, and he is a widely published author on business and technology issues and a frequent speaker at IT industry events.

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