Accelerate Self-Service Analytics with Data Virtualization (DACH)

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September 23
11:00 CEST
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Chris Fitzpatrick
Chris Fitzpatrick Partner Sales Engineer Denodo
Michael Shabanzadeh
Michael Shabanzadeh Managing Director Ergoman

 2021/09/23

There’s a growing number of large-scale enterprises that need to perform targeted data analytics on multiple data sources. The integration of data from multiple sources is a challenging task. Data virtualization presents a modern approach to data integration. Unlike ETL solutions that replicate data, data virtualization leaves the data in source systems, simply exposing an integrated view of all the data to data consumers. As business users drill down into reports, data virtualization fetches the data in real time from the underlying source systems. Data virtualization proves that connecting to data is far superior to collecting it.

Data can reside in multiple data marts. And data virtualization can perform data integration seamlessly with such BI tools as Tableau, PowerBI and IBM Cognos® Analytics. Data virtualization can connect to data wherever it resides and provides the ability to view, access, manipulate and analyze data without the need to know or understand its physical format and location. Data virtualization creates virtual tables to join data from different data sources, then allows running queries against the resulting virtual table.

In this webinar, we’ll demonstrate how data virtualization can be achieved on various data sources with an Oracle database hosted on Amazon Web Services with self-service analytics on Cloud, and improve performance of your reports and dashboards. Join our experts to learn:

  • The concept of data virtualization and challenges faced by business users
  • How data virtualization enables self-service analytics
  • Overview of the highlight features in Tableau, PowerBI and IBM Cognos® Analytics
  • How to create connections from databases hosted on multiple environments
  • How to create views and publish data to your current project

What's Next?

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