Transition from SLAVE DB to Aggregated Database

The Challenge with SLAVE DB

• Complex Queries: Reporting on SLAVE DB required long, complex queries across large datasets.
• Performance Issues: Queries took significant time to execute, resulting in slower reporting.
• Real-time Constraints: Transactional data was highly dynamic, making it difficult to run analytics in real-time.
• Resource Consumption: Querying directly from SLAVE DB put unnecessary load on the transactional system, affecting its overall performance.

Key Advantages of the haqdarsh_aggregates Database

• Improved Performance: Pre-aggregated data reduces computational overhead making query responses to reduced from minutes to seconds.
• Reduced Load on Transactional Database: Offloading reporting queries to the aggregated database prevents the SLAVE DB from being overburdened by heavy analytical queries.
• Simplified Reporting: Standardized metrics and dimensions are available, allowing for easy access and analysis by business users.
• Scalability: Aggregated data can be scaled easily by adding more dimensions or granularities as business needs grow.
• Better Insights and Decision-Making: By having readily available summarized data, stakeholders can quickly derive insights, make timely decisions, and respond to market dynamics more effectively.

Future Considerations

• Integration with BI Tools and customized front-ends: Further streamlining of reporting with integration to tools like Power BI and customized front-end dashboard on React for self-service analytics.
• Real-time Data Aggregation: Investigate the possibility of near-real-time aggregation for use cases requiring more dynamic data.

Use Cases and Examples

• Sales Reporting: Instead of querying the transactional database for every sale, aggregated data provides daily summaries for regions, products, or sales reps.
• Customer Insights: Analyze daily active users, churn rates, and customer behaviors quickly and easily, without digging through raw transaction logs.