RESEARCH & RESOURCES

Seven Steps to Faster Analytics Processing with Open Source

TDWI Speaker: David Stodder, TDWI Research Director

Date: Thursday, December 17, 2015

Time: 9:00 a.m. PT, 12:00 p.m. ET

Webinar Abstract

Excellence in analytics is a competitive advantage in nearly all industries. For this reason, organizations need their data scientists, business analysts, and business users to be able to access and interact with more sources and more types of data than ever before. The Hadoop ecosystem is flourishing, producing innovative technologies and frameworks such as Apache Spark, Apache Apex, and more that are becoming important for providing processing speed and power as well as data integration and preparation capabilities for fast, visual, and interactive analytics.

Join this Webinar to learn about how to develop a strategy for harnessing open source and open standard technologies to meet the needs of analytics – both advanced analytics and self-service, visual analytics and business intelligence (BI) designed for nontechnical users. The Webinar presentation and roundtable discussion will cover trends such as real-time stream processing and analytics, interactive and iterative analytics on Hadoop data, big data integration and preparation, and more.

The Webinar will discuss how open source technology trends fit data-driven business objectives that rely on democratizing analytics and enabling greater analytic speed, data diversity, and power. Along with a presentation by TDWI Research, the Webinar will include a panel discussion with four leading technology providers.

This Webinar will discuss:

  • Business demand for faster and more powerful processing for analytics
  • How open source technologies are enabling more interactive and iterative analytics on Hadoop data
  • How open source stream processing and stream analytics support real-time requirements
  • Open sources technologies and trends in data integration and preparation
  • Strategies for meeting expanding needs for both democratized and deeper analytics

David Stodder

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