Centralized Data Management for Timely Business Decisions

Background

Symphony Solutions partnered with GOAT Interactive to develop a centralized data management solution for effective understanding and growth of their sports betting and iGaming product. This was achieved through migration of data to Google Cloud, building a cloud data warehouse and data lake, and real-time analytics and reporting using BI dashboards like Data Studio and Looker. Integration with CRM tools provided valuable insights into market behavior and business performance metrics, enabling GOAT to make timely data-driven decisions. The end result was a reliable, scalable, and maintainable solution that helped GOAT become a top operator in the African market. 

Server-side tagging implementation helps us to control what kind of data is sent to our vendors helping us to better optimize paid advertising campaigns.  It helps us to keep our performance KPI’s intact by reducing the load time of our web pages giving our customer’s a better user experience using our products

Shane Courtney, Director of Development 

Client

GOAT Interactive is a part of the Editec Group. Its goal is to become the number one operator in the African market. It aims to fuse the world of football and betting, creating an authentic, highly engaging community of sports fans who love the thrill of a bet. The brand is closely partnered with renowned football club brands and leverages these partnerships to provide a unique player experience, enabling GOAT to provide unique betting propositions, content, and events to the rapidly growing African market – an experience that brings fans closer to clubs, leagues, and the sport they love. 

Challenges

Our client, being one of iGaming industry’s leaders, is receiving large amounts of data on market behavior, company business performance metrics, as well as some historical data. However, when they approached Symphony Solutions, this data was not centralized. Thus, they were not able to correlate metrics to drive some insights and make the right business decisions on time. 

The list of tasks included the following: 

• Migrate large amounts of data (about 10 TB) from on-premises databases. 
• Build a cloud data warehouse (DWH) and Data Lake on top of the Google Cloud Platform (GCP) ecosystem. 
• Create BI dashboards using Data Studio and Looker. 
• Implement email reporting services to data stakeholders. 
• Integrate DWH with CRM tools like Atlas, Optimove, and Raventrack. 
• Implement real-time data streaming and analytics within DWH. 

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Solution

Based on the client’s cloud preferences, Symphony started working on building a data warehouse on Google Cloud. The initial stage was creating PoC, which was followed by adding detailed reports, migrating all data, and enabling complex integrations with CRM providers, thus empowering users’ data enrichment to be able to conduct more effective behavior analysis. 

Based on the client’s request, Symphony’s team set out to work on developing the following: 

• DWH and Data Lake have been built on top of BigQuery and Google Cloud Storage / Dataproc, respectively 
• Cloud Composer is used for ETL pipelines orchestration 
• Data Studio and Looker are used for BI dashboards 
• Dataflow is used for real-time data streaming and analytics (in progress) 

As the next phase is currently in progress, the work is evolving from batch processing to real-time data streaming as a way of improving the client’s services and automating business processes. 

Result

The client obtained an automated, reliable, and scalable solution. Their business process became robust and predictable with the built cloud data warehouse, including integrations with different CRM tools. The current list of outcomes includes the following: 

• Automated cloud data warehouse with batch processing and real-time data analytics features. 
• Our team accomplished 20 different important reports for 15 countries. 
• We built more than 22 Data Studio dashboards. 
• We built up to 10 models containing 30+ explorers within Looker. 
• Client Administrators can perform analytics in real time. 
• Cloud ecosystem allows us to get all the data in one place and orchestrate ETL pipelines in a unified way, and prepare on-demand OLAP cubes. 
• Migrated more than 10TB of external data. 
• A reliable, scalable, and well-maintainable solution. 

Currently, we are working on developing and extending real-time data streaming and providing support for the existing solution. 

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