Business Challenges and Objectives

The client identified the need for a more appropriate cloud platform to align with their business demands, as Teradata proved to be lacking in terms of performance, cost-effectiveness, and features when compared to Microsoft Azure.

The Solution

• TekLink successfully migrated the initial data set to Azure Data Lake Store.
• This migration was accomplished by leveraging Spark data frames and implementing the designed infrastructure of Azure Data Lake Store.
• This deployment enabled the utilization of Spark’s fast data frames, enabling parallel processing and distributed computing capabilities.
• After performing data transformations and converting it into the required reporting format, the TekLink team loaded the filtered data into the Client’s Azure Data Lake Store.
• The loaded files were then directly analyzed in Power BI, utilizing the querying capabilities directly from Azure’s Data Lake Store.

Business Outcomes and Benefits

• The project successfully met its goals and surpassed the performance expectations of our Client.
• The processing time for Azure’s Load and Transform activities was significantly reduced compared to the earlier run-times in Teradata, resulting in faster data processing.
• The complexity of the system was considerably reduced from the original Teradata model, simplifying the overall architecture.
• By leveraging Databricks’ pay-as-you-go service, our Client effectively minimized their processing costs in comparison to Teradata.
• TekLink’s Global Delivery Model played a crucial role in reducing migration costs and ensuring continuous support for the analytics platform.