Optimize “All Data” with a Modern Data Warehouse Solution
summary
Shows concrete, tested approaches: streaming pipeline using Azure Event Hubs -> Azure Stream Analytics -> Azure ML for live Twitter sentiment analysis and a demoed Azure website; data warehouse choices from Azure SQL DW and PolyBase to SQL Server 2016 features (columnstore, stretch, temporal, Always On read‑secondaries); monitoring with SQL Sentry/SolarWinds; a troubleshooting example finds a 12 TB database stalled by SAN throughput of 10 MB/s vs 200 MB/s and demonstrates configuration and recovery steps that actually work.
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chapters (11)
- 0:00Intro
- 0:41Technical Assistance
- 7:39What is Data Lifecycle Optimization? data and insight platforms and solutions
- 8:55Architecture and Configuration • What Needs to be Accomplished
- 13:43Determining Technological Fit
- 17:42Availability and Continuity
- 27:23Performance & Optimization • Proper Configuration • Monitoring Your Environment
- 35:19Combining Platforms to Optimize your Business
- 38:39Components of an insights platform
- 45:25Finding value in your data..
- 49:06How do you approach finding the value?
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