Business Objective

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

The Solution

• TekLink migrated the initial data set to Azure Data Lake Store.
• The TekLink team enabled this migration by designing and the Azure Data Lake Store by using Spark data frames.
• By this deployment, we enabled Spark’s fast data frames with parallel processing and distributed computing.
• After transforming and converting the data into the required format for reporting, the team loaded the filtered data into our Client’s Azure Data Lake Store.
• The files were then analyzed in Power BI making a direct query from Azure’s Data Lake Store.

Key Project 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.
• TekLink’s Global Delivery Model ensured that the cost of migration reduced considerably and provide room for continued sustainment of analytics platform.