Webinars - Featured Articles

December 14, 2015

Webinar - Upcoming Webinar Will Focus on Big Data Democratization and Virtualization


Data virtualization has basically leveled the playing field when it comes to handling and managing big data. This “democratization” is a phenomenon happening throughout the IT industry as users drive trends and increasingly demand more insight and analytics to help guide decision making and operations.




“Democratizing Big Data Using Data Virtualization” will be the subject of a webinar tomorrow featuring input from data virtualization experts Denodo along with Forrester (News - Alert) Research and Hortonworks. Guest speakers will share information and guidance for tackling big data projects during the event, which will take place at 2 p.m. ET on December 15.

The speakers will cover the basics of big data, analytics and data integration to help companies succeed with deploying their big data projects. Ravi Shankar, CMO of Denodo (News - Alert), will examine the cost savings and efficiencies of virtual integration of big data with other enterprise data. These include data warehouse, CRM and ERP applications, all of which need to be properly integrated with big data for true data democratization along with valuable business insights.

Noel Yuhanna, principal analyst with Forrester Research (News - Alert), will discuss real-time Hadoop, machine learning accelerated solutions, simplification and automation and security for big data projects. Matthew Morgan, VP of product and alliance for Hadoop pioneers Hortonworks, will focus on how to get started with Hadoop for data discovery, single view and predictive analytics of big data.

Last month Denodo announced a partnership with Kadenza through which the company will offer a logical data warehouse solution using the Denodo Platform. The combined offering will give Kadenza customers deeper insights across all enterprise data sources.

Meanwhile, last week Hortonworks announced advancements to its Hortonworks Data Platform with the addition of in-memory analytic capabilities using Apache Spark 1.5.2. The updated platform will support Spark SQL and Spark Streaming in an effort to derive greater value and insights from big data.




Edited by Kyle Piscioniere