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How a Unified Semantic Layer Can Help Business Intelligence

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Research shows that the average enterprise has at least 6 to 10 Business Intelligence tools.  Microsoft Excel, the world's most prevalent analysis tool is used by 1 Billion users.

Other companies like Tableau, Qliktech, MicroStrategy or Business Objects have had great success too.   

However, there is one key issue with a heteregeous BI environment: each tool uses a different protocol so data has to be customized to work with each BI tool.    

For instance, Excel uses MDX and Tableau prefers SQL.   What if your company uses new tools like Looker or even open-source tools like Apache Zeppelin? 

How can your deliver one version of the truth to all users, regardless the tool they use? This post helps you get there.  

In this short video below you can quickly learn and understand:

  • How a unified semantic layer helps your organization define data views once, and deploy them to all business intelligence tools, in a governed manner.
  • Why one single view of the data enables your team to provide self-service, without compromising insight consistency or governance.
  • How you can marry SQL, MDX and Spark to provide live self-service analytics at top speed and unlimited scale.
  • How Virtual OLAP lets companies benefit from the speed benefits of aggregates without compromising transaction-level and atomic data access.
 

 

If you're interested in reading more about doing BI on Hadoop, here are a few additional resources to check out!

We hope this quick overview was helpful to you and your team. If there are other questions you’d like us to answer, please feel free to add them into the comment section of this blog.

Last but not least, subscribe to this blog to get more helpful tips about Hadoop and BI on Hadoop!


Topics: Hadoop, Business Intelligence, Big Data

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