Improving the SSRS Performance with a Comprehensive Snowflake Data Warehouse

Enhanced accessibility to large datasets from SSRS Reports

The client is a global provider of development, production, technical expertise and services to a wide range of metal, steel, and manufacturing industries.

Business Objectives

The client wanted to implement a cloud data warehouse solution to improve performance in accessing large datasets by means of SQL Server Reporting Services (SSRS) Reports on relevant industry sales. The performance of SSRS was very poor while generating the reports from SQL Server Analysis Service.

What services did Data-Core Systems provide?

Our team’s primary focus was to load data into Snowflake’s staging tables from a CSV file, populate Snowflake’s data warehouse tables from the staging tables, and use Snowflake computing to generate the calculated/aggregated fields. The information would then be shown through the SSRS Report. This approach, we felt, would improve the overall performance of the reporting process.

Activities we engaged in

  • Understand and analyze the characteristics of the data.
  • Create Snowflake’s staging tables to load data from a CSV file.
  • Load data from a CSV file to Snowflake’s staging tables.
  • Create the data model (fact/dimension) inside Snowflake’s data warehouse.
  • Populate the fact/dimensions from Snowflake’s staging tables using Pivot Query.
  • Create views using the Snow SQL windowing function.
  • Connect the views with SSRS and generate the reports with improved performance.

Strategic Benefits

Data-Core’s successful implementation of Snowflake’s cloud data warehouse improved the reporting performance of the SSRS Sales Reports by approximately ten times, saving the client time and money substantially. In addition, our team at DataCore Systems provided reports using Power BI, and the performance was a notch better than what was achieved with SSRS. This was a value-added service provided to the client.

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