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Combining The Data In Denodo Platform.

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Denodo: A  data virtualization platform

Data virtualization is a core technology that enables modern data integration and data management solutions.

Factors of data virtualization:

  • Connect, introspect, and govern any data source with zero data replication: Quickly connect disparate structured and unstructured sources. Catalog your entire data ecosystem. Data stays in the sources and it is accessed on-demand, with no need to create another copy.
  • Combine and integrate into business data views: Build data models that suit the needs of the consumer, even across multiple sources. Hide the complexity of your back-end technologies from the end users.
  • Consume and secure data views in multiple formats: The virtual model can be secured and consumed using standard SQL and other formats like REST, SOAP, and OData.

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Combining the data

With the data sources and base views in place we are in a position of starting to combine all the data. The first steps are to have a denormalized, standardized view of each data source so we get a set of base business entities.

Step1:

  • Right-click over the “bv_wo_customer” folder and select New > Join.

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Step2:

The “customer” view will get dragged onto the workspace.

Step3:

          Drag the “bv_wo_orders” view onto the workspace.

 

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Step4:

          Connect the “customer_code_internal” column from the customer table to the “customer_code” column of the orders table.

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Step5:

          In the Output tab, remove the “customer_code_internal” and “customer_code” columns

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Step6:

          Click save.

 

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Step7:  With these steps we have created a new view that contains the standardized names for each customer_code, instead of the wrong ones that we originally had. To check that everything is working properly click on  and then Execute  again:

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Here we have successfully combined the customers and order data in denodo.

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Himanshu Padole

Himanshu Padole works at Perficient as an Associate Technical Consultant. He has over 1 year of experience in ETL tools – SSIS, Denodo, Informatica, Talend, and SQL. He also has a good knowledge of Python, ADF, and Databricks.

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