Overview
The client is a prominent health and fitness club franchise operating across 50 countries in over 5,000 locations with more than 3,000,000 members worldwide.
Challenges
The client’s increasing data volume led to concurrency challenges during data read and write operations, affecting data consistency and operational efficiency. Complex ETL processes hindered data processing efficiency, requiring a robust solution for smooth aggregation in the Gold layer to streamline analytics and reporting. Delays in data availability impacted report generation and incorporating new data sources was cumbersome due to rigid schemas, necessitating a unified platform for analytics, business intelligence (BI), and machine learning for flexibility.
Solution
Contata addressed the challenges by leveraging Databricks. We implemented Delta Lake as part of its Lakehouse architecture, combining the best features of data lakes and data warehouses.
Delta Lakehouse
The implementation of Delta Lakehouse ensured schema integrity on write, addressing the concurrency issue during data read and write operations. The adoption of the open Delta Parquet file format facilitated efficient CRUD operations and time travel features, enhancing the gold layer’s aggregation process. Optimization features like data compaction and caching significantly improved query performance, contributing to a more efficient storage system.
Databricks Lakehouse
Utilizing Azure Data Lake Storage Gen2, Databricks Lakehouse provided a key solution for cost-effective and scalable storage, addressing challenges related to data accessibility and volume. The unified analytics platform accommodated structured and semistructured/unstructured data, serving as a single platform for analytics, business intelligence, and machine learning on top of Delta Lake. The schema-on-read approach ensured enhanced flexibility, while robust data governance features addressed stringent security standards, ensuring data integrity.
Unity Catalog
The integration of Unity Catalog simplified metadata management, aiding in the process of data discovery and maintaining consistent governance practices. Unity Catalog’s integration with Delta Sharing enhanced secure data sharing, fostering collaboration across organizations and platforms. Data masking techniques were also implemented to ensure data security, protecting sensitive information and complying with privacy regulations.
Benefits
- Simplified Implementation: Faster data load and pipeline creation due to the streamlined processes enabled by Databricks and Delta Lake.
- Seamless Migration: Reporting table code seamlessly migrated from SQL to Databricks Notebook, ensuring a smooth transition and continuity in reporting.
- Cost-Effective Solution: Databricks provided a cost-effective and faster solution compared to ADF + SQL, contributing to financial savings for the client.
- Versatile Data Storage: Increased ability to store various data btypes without concerns about cutting table sizes, enhancing data storage flexibility and adaptability.