You are here

In the Media

Our award winning data virtualization platform is regularly featured in the world's leading business and IT publications worldwide. 

 

 

 

 

What is Data Virtualization and Why Does It Matter?

Bernard Marr, internationally best-selling business author, keynote speaker and, one of the world’s most highly respected voices anywhere when it comes to data in business, discusses the importance of data virtualization in this digital age.

Improve Customer Service and Intelligence with MDM and Data Virtualization

Salah Kamel, CEO and Founder at Semarchy and Ravi Shankar, CMO at Denodo explain how MDM and data virtualization can work in tandem to provide a complete, contextual view of the customer.

“Above the Trend Line” – Your Industry Rumor Central for 2/27/2017 from insideBIGDATA

In this column, insideBIGDATA captures the announcement of the strategic partnership between Denodo and Semarchy to collaborate in marketing, partner and market development, as well as in sales and research and development in the combination of master data management (MDM) and data virtualization.

Bringing Context to IoT Data

Just as ingredients for a meal are selected and combined in a meaningful way to create flavors, textures and other qualities, assorted IoT data must be blended, and combined with other relevant data – such as master data – to bring the context necessary for comprehensive insights. This article is the first in a two-part series written by Lakshmi Randall, Director of Product Marketing at Denodo.

Denodo – Predictive Analytics: 2017’s Hottest Data Trend

Ravi Shankar, Chief Marketing Director at Denodo explains how a world with predictive analytics in place is a world of much more than just accurate weather. Decreased disease, improved automation efficiency, and heightened cybersecurity are just a few of the potential benefits. However, these benefits can only be realized by deploying a Big Data fabric powered by data virtualization. With Big Data fabric, predictive analytics will indeed be the hottest data trend in 2017.

4 Data Virtualization Vendors To Watch in 2017

In Gartner’s recent Market Guide for Data Virtualization, the technology research giant goes into detail describing what kind of an impact Data Virtualization will have on the enterprise in the years to come. As a strategic planning assumption, Gartner projects that by 2020, 35 percent of enterprise organizations will implement Data Virtualization in some form as a more forward-thinking option for Data Integration.

Seacoast Bank Cashes in on Data Virtualization

Thanks to data virtualization, Seacoast Bank has reduced the amount of time required to create a new reporting application from what used to take between eight months and a year using ETL tools down to four or five months. 

Big Data Fabrics Emerge to Ease Hadoop Pain

The rise of cloud repositories also plays heavily into the emergence of big data fabrics, according to Ravi Shankar, chief marketing officer of Denodo Technologies, which was one of 11 big data fabric vendors profiled in Forrester’s recent report.

The Power of Data Intermediaries

Ravi Shankar, Chief Marketing Director at Denodo explains how a data intermediary is required to act as a "middle man" to business users consuming data on a regular basis. This "middle man" must provide access to all of the necessary enterprise data without any worry about which systems they come from or what format they are stored. Data virtualization is a technology that is perfectly suited to playing the role of this data intermediary.

Key Takeaways: Forrester Wave Big Data Fabric, Q4 2016

Enterprise technology analyst house Forrester Research has recently released the latest version of its Big Data Fabric Wave Report for Q4 2016. In their 26-criteria evaluation of Big Data Fabric solutions, Forrester researchers Noel Yuhanna and Gene Leganza identified the nine providers whom they consider most significant in the category – Informatica, Talend, IBM, Paxata, Trifacta, Oracle, Denodo, Syncsort, SAP, Global IDs, and Waterline Data – then researched, analyzed, and scored them.