Transforming Data Warehousing with Google Cloud Platform

Spatialedge designed and implemented a data warehousing solution for a client in the retail sector, leveraging various Google tools. The solution ingested multiple sources of on-premises data into BigQuery, establishing it as the client’s primary data warehouse and reporting system.

The Challenge

The client needed to migrate their data warehouse from an on-premises system that struggled to handle the volume and complexity of incoming queries. Additionally, they sought to enhance the flexibility and accessibility of their system, allowing for easier data sharing with other internal companies and external auditors.

The Solution

Our comprehensive solution was structured around two key components:

1. Data Infrastructure Development on Google Cloud Platform

The client's strategic shift to Google Cloud Platform (GCP) provided the foundation for a robust data infrastructure, essential for data warehouse modernisation. BigQuery Served as the primary data warehouse, ensuring high performance and scalability for handling large data volumes and complex queries. Cloud Composer Managed data pipelines efficiently, enabling seamless data flow and integration across different stages of the data lifecycle.

These technologies were selected for their performance and compatibility with the client’s existing data systems, enabling seamless data flow and management in a dynamic environment.

2. Operational Integration and Continuous Support

Integrating the data warehouse framework into the client's operations involved strategic steps to ensure minimal disruption and maximal utility. Data pipelines and tools were designed to integrate smoothly with the client’s existing systems. The system was designed for ongoing adjustments and expansions, with continuous support and iterative enhancements to adapt to new challenges and opportunities.

Outcomes and Benefits

The new data warehouse delivered several advantages over the existing system. The new system provided unprecedented scalability and operational efficiency, enabling the client to adopt more accurate and efficient data processing models. The cloud-based infrastructure allowed for scalable and flexible data processing and integration, accommodating the client’s growth and increasing data complexity. The centralised data pipeline management reduced redundancy and streamlined the development process, significantly decreasing the time from data ingestion to reporting.

The client later commented that  the system built by Spatialedge was much more efficient than their existing solutions. The client’s exact comment was as follows:

“To test the new system, I ran a query on both the old and new system. When I returned from getting a coffee, I was surprised to see that BigQuery returned the results in under a minute! After a day, I cancelled the query on the old system, because it was just not going to finish. That was when I realised the power of the cloud.”

Challenges and Considerations

The project encountered challenges primarily related to integrating new technologies with the client’s legacy systems. Initial lack of technical specifications and rigid older systems posed hurdles, but these were progressively overcome through strategic adjustments and collaboration between Spatialedge and the client’s internal technology providers.

Conclusion

By adopting this cloud-based data warehouse approach, the client is well-positioned to enhance its operational capabilities and maintain a competitive edge in a rapidly evolving market. This project underscores Spatialedge’s expertise in navigating complex technical landscapes and delivering innovative solutions that drive tangible business outcomes.