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Azure SQL Data Warehouse Offered Database Performance Improvement

The customer is a leading financial services company that focuses on lending, insurance, wealth management, and asset management. They were looking for a flexible solution that helps them upscale and downscale database resources according to the requirements.

The Challenge

The customer’s SQL database was installed on-premises on a standalone physical machine. The SQL database was dedicated to handling different requirements such as CIBIL data and alternate data. It served the purpose of collecting data from different resources and processing the same. However, the customer faced challenges in scaling the database resources when needed, which in turn caused process inefficiencies.

Key Challenges Involved:

  • Multiple jobs with monthly deadlines such as CIBIL Bureau and scheduling alternate data for processing were taking much time, nearly 12 hours time in an on-premises server.
  • A limited storage space, 5TB, was allocated in the on-premises server. For data consumption beyond this entailed a time-intensive procurement process. Once allocated, the resources couldn’t be scaled down.
  • The customer could carry out data processing only through SSIS. Also, They were unable to create pipelines for data processing.
  • Heterogeneous data sources, such as storage, google queries, and APIs, could not be connected.

The Solution

The customer partnered with Blazeclan for implementing an optimal solution that helps them upscale and downscales their database resources as per their need. The allocated hardware for the customer’s SQL server included 512 GB RAM and 5 TB storage. Blazeclan proposed the customer with a solution that would shift their on-prem standalone SQL server to Azure SQL data warehouse.

The Shift From On-Prem Standalone SQL Server to Azure SQL Data Warehouse

  • Moving SQL database from on-premises to Azure SQL data warehouse helped the customer to significantly reduce the data processing time by boosting speed. The solution leveraged Azure Data Factory was for data processing.
  • The solution helped the customer to scale storage requirement without any downtime.
  • The customer was able to connect multiple heterogeneous data sources such as storage service, google queries, and APIs.
  • The solution allowed consumption of different data sources such as the alternate data, which included geographical data and customer details, and CIBIL data while meeting storage requirements.

Benefits Achieved by the Customer

  • The solution allowed the customer to store massive amounts of data, up to 100TB, compared to the 5TB, confined, on-prem database.
  • The solution enabled the customer’s systems to be Fully Managed by Microsoft, which removed the hassles of management and maintenance.
  • The customer saw a considerable improvement in the performance of their database by moving to the Azure SQL Data Warehouse.
  • Azure SQL DW enabled the customer to pause and resume their service as per requirements, which in turn led to cost optimization.
  • The solution allowed the customer to scale down compute and storage in non-production hours and scale up at times of high demand.
  • The new environment offers the customer with support to multiple, heterogeneous data sources.

Tech Stack

Azure Synapse SQL Pool SQL Server