Summary
In this module, we explored how scalable semantic models enable organizations to analyze and report on large, complex data sources with ease. Microsoft Fabric allows for optimal consumer experiences in Power BI reports by handling high-volume, large-scale data efficiently. To address these challenges, we covered:
- Optimizing based on storage mode.
- Handling large data techniques.
- Designing star schema and relationships.
- Optimizing calculations using variables, DAX functions, and dynamic elements.
Without Microsoft Fabric, the analytics team would rely on manual, nonscalable reporting solutions, resulting in time-consuming data processing, increased complexity, and limited ability to handle large datasets efficiently.
By designing scalable semantic models at the start, you can improve analytics performance and efficiency. These techniques enable timely and accurate reporting, better decision-making, enhanced operational efficiency, and overall increased satisfaction.
Further Reading: