Sunset-ed Teradata with Microsoft Azure for Better Performance and Cost Savings

Sunset-ed Teradata with Microsoft Azure for Better Performance and Cost Savings

About the Client

Our client is a Global Consumer Package Goods of Tobacco and other related products.

Business Challenge

The client needed a cloud platform better suited for the business demands as Teradata lagged in performance, cost, and features compared to Microsoft Azure.


Approach and Solution

TekLink designed an Azure Data Lake store and leveraged our Client’s Azure Databricks using Spark data frames to migrate initial data set into the Azure Data Lake Store. By doing this, we leveraged Spark’s fast data frames with parallel processing and distributed computing.

Once the data was transformed and converted into the required format for reporting, the team loaded the filtered data into our Client’s Azure Data Lake Store. These files were then analyzed in Power BI making a direct query from Azure’s Data Lake Store.

TekLink’s Global Delivery Center was leveraged to reduce the cost of migration and for continued sustainment of analytics applications.


Outcome and Benefits

The project achieved its goals and exceed the performance expectations of our Client.

  • Processing time for Azure’s Load and Transform activities is reduced to a fraction of earlier run-times in Teradata.
  • The complexity of the system was decreased significantly from the original Teradata model.
  • Leveraging Databricks’ pay-as-you-go service, our Client minimized their overall processing cost as compared to Teradata.


In the end, Azure has demonstrated better performance, easier to manage, and cost savings.

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