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Pentaho BI Developers sharing approaches to get rid of MDX using Pentaho development and data integration

The Multidimensional Expressions (MDX) is a query language like SQL; however, if you have learnt SQL before and want to learn to write advanced MDX; you may need to invest your time while learning MDX and its debugging method. It’s crucial to add latest skills and knowledge points for writing MDX.

Problem faced by Pentaho BI developers

Under Pentaho development, developers need to use Mondrian approach to enhance the reusability and performance. With Mondrian, you can perform lot of caching of the data. Also, it provides you the flexibility to create an abstraction between BI components and database. The difficulty level is high for novice MDX learners as the Syntax is not as similar as SQL.

You have to be good at writing transformations using Pentaho Data integration to get rid of writing MDX.

How developers can solve the problem?

Pentaho BI developers need to write BI components using Mondrian OLAP and for this, they need to acquire MDX skills and knowledge. Here’s how the process flows-

How the solution approach should be made?

Developers can create an OLAP schema in easy way using Pentaho Schema Workbench. After building the schema and testing its performance, Pentaho developers can use it in data integration tool and develop end solution without any strict requirement of writing lengthy MDX.

Next they need to double click on the Mondrian input and make a DB connection-

After that, they need to browse the schema file that already has developed by them in schema workbench-

Then they just need to write basic MDX that will help in fetching required Columns-

Once the fetching of columns is done, developers can start formatting the data, putting business logic as per the requirement and complete the transformation. They need to change the catalogue path to the server path where they want to put the schema file.

And it is done. This is how Pentaho BI ETL developers can get rid of MDX using pentaho data integration approach as discussed above.

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