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Best Data Virtualization Solution


The overall goal of data integration is to achieve a complete view of enterprise data across disparate data environments.

However, with unstructured and structured data housed across operational and analytical systems, a range of technologies to handle it all, including Hadoop, NoSQL, and relational database management systems, the danger is that organizations are moving further than ever from that objective.

One approach that has come to the fore to overcome data silos and revive the original goal of the data warehouse is data virtualization. With this technology, data from across the enterprise is abstracted into a common service fabric. 

Data virtualization provides organizations with the ability to allow the business and IT sides of organizations to work closer together in a much more agile fashion, and helps to reduce the complexity. “It also gives us the ability to scale as necessary,” observed Anne Buff, business solutions manager for SAS best practices at the SAS Institute, during Data Summit 2015.

Virtualization addresses the organizations’ need to achieve a comprehensive view of their data, while avoiding the need to rip and replace physical systems already in place.

Successful solutions will offer enterprises agile development, a secure virtual data layer, and real-time data access and provisioning.

HERE ARE THE WINNERS OF THE 2015 DBTA READERS' CHOICE AWARDS FOR BEST DATA VIRTUALIZATION SOLUTION

Winner:

Denodo Data Virtualization Platform

Ravi

Winners' Circle by Ravi Shankar, Chief Marketing Officer

Organizations have long used data as a strategic tool to better run their businesses. But making business-critical information available in a timely fashion is not easy because relevant data resides in disparate and, often, siloed systems spread across the enterprise. Business users waste time piecing together the data from these different systems and then correlating it, while IT teams try to automate the process using legacy data integration techniques like extract-transform-load (ETL), which is time-consuming and expensive...read on.



Finalists:

Red Hat JBoss Data Virtualization

Oracle Database 12 Multitenant


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The 2015 DBTA Readers' Choice Award Winners

Posted August 04, 2015

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