bizacuity

Modern BI Ecosystem for a Popular Sports-betting company

About Client

One of Poland’s most popular sports betting companies that kickstarted operations in 2019

Challenge

The client wanted to build an Enterprise Data Warehouse on Microsoft Azure to support their rapidly expanding business

Our Solution

  • The client was using PostgreSQL which was primarily designed as a row-based RDBMS which would inevitably affect the performance and scalability of the database.
  • Hence, data was replicated from PostgreSQL to Azure SQL using Azure Data Factory.
  • An Enterprise Data Warehouse was built using Azure SQL Server configured with continuous refresh for shorter latency (near real-time updates as new data becomes available)
  • Reports were made available instantly for the end users using SSRS for visual reporting
  • An additional capability of Auto Reset was included within the architecture to ensure the client’s development team could be more focussed on other core activities. The auto rest feature instantly notifies the team incase of any failure of Azure Jobs.

Azure SQL: A scalable, reliable and high performance RDBMS solution

Azure Data Factory: A data integration tool that is used for orchestrating data integration and transformation workflows

Azure SQL Server: A data warehousing solution known for its security and hybrid cloud capabilities

SSRS: Widely used Microsoft tool for its powerful and flexible reporting solutions

Outcome

  • A modern, reliable and highly secure Enterprise Data Warehouse and Reporting System completely built on Azure infrastructure
  • SSRS reports were made available almost instantaneously to enable quick decision making
  • An audit framework was developed for auto reset feature that provides the developers with answers to questions like: at what stage of the pipeline the failure happened, which data got missed and where it should resume etc straight to their inbox.
    Source failures or data unavailability is a common issue with any and all EDWs, instantly notifying the team with the details of the issue drastically decreased their workload.
  • Around 85 tables were replicated from PostgresSQL to Azure SQL for reporting and analysis.

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