Billions of records: the real success story using Microsoft Power BI Embedded
summary
Architecture brings 1.4 billion rows and ~1M daily smart‑meter points into a compressed in‑memory cube that serves embedded visuals in seconds, moving heavy work into Azure Databricks (ETL), a staging SQL database, and Azure Analysis Services with Power BI Embedded for fast client queries. Incremental loads run minutes daily, ML predictions cycle through Azure ML, row‑level security enforces tenant access, the production system ships in ~2 months for a pilot that is ~10× cheaper and reports ~30× speedup over the previous approach.
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chapters (39)
- 0:00Intro
- 4:41Irinas background
- 5:31District heating
- 6:16Smart meter
- 6:41Data collection
- 7:13Huge opportunity
- 7:49Large enterprises
- 8:42Near realtime data
- 9:21Traditional approach
- 10:13Response time
- 10:24Data handling
- 10:43Caching strategies
- 11:34Challenges
- 12:24One service
- 13:20Visualization tool
- 14:25Microsoft Power BI
- 15:45What is Power BI
- 17:16Power BI Desktop
- 20:23Power BI Reports
- 21:31Application overview
- 24:00Architecture overview
- 25:41Data transformation process
- 26:18Azure Data Factory
- 27:39Star Schema
- 32:20Data sources
- 35:43Power BI Report
- 37:32Config
- 39:03Multilanguage support
- 40:31Live demo
- 41:16Filters
- 42:27Data hierarchy
- 43:28Embedding options
- 47:05Application authentication
- 48:04RowLevel Security
- 49:15Authentication
- 50:41Process overview
- 51:38Cost management
- 53:38Benefits
- 56:02Conclusion
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