| 01. Performance Optimization.mp4 | 8.6 MB | ||
| 01. Performance Optimization.vtt | 5.6 KB | ||
| 02. Optimizing the Lakehouse.mp4 | 3.7 MB | ||
| 02. Optimizing the Lakehouse.vtt | 3.1 KB | ||
| 03. Demo - Lakehouse Delta Table Optimizations.mp4 | 15.1 MB | ||
| 03. Demo - Lakehouse Delta Table Optimizations.vtt | 7.1 KB | ||
| 04. Performant Pipelines.mp4 | 5.1 MB | ||
| 04. Performant Pipelines.vtt | 4 KB | ||
| 05. Demo - Parallel Pipelines.mp4 | 4.3 MB | ||
| 05. Demo - Parallel Pipelines.vtt | 2.4 KB | ||
| 06. Warehouse Issues.mp4 | 3.3 MB | ||
| 06. Warehouse Issues.vtt | 2.5 KB | ||
| 07. Demo - Warehouse Performance Queries and Statistics.mp4 | 10.9 MB | ||
| 07. Demo - Warehouse Performance Queries and Statistics.vtt | 4.4 KB | ||
| 08. Additional Fabric Errors.mp4 | 7.8 MB | ||
| 08. Additional Fabric Errors.vtt | 6.3 KB | ||
| 09. Demo - Configure Compute for Environment.mp4 | 14.4 MB | ||
| 09. Demo - Configure Compute for Environment.vtt | 5.9 KB | ||
| 1. Eventhouse Issues.mp4 | 7.5 MB | ||
| 1. Eventhouse Issues.vtt | 5.5 KB | ||
| 1. Monitoring Fabric.mp4 | 7.5 MB | ||
| 1. Monitoring Fabric.vtt | 5.5 KB | ||
| 1. Pipeline Errors.mp4 | 4.4 MB | ||
| 1. Pipeline Errors.vtt | 3.9 KB | ||
| 10. Query Tools and Steps.mp4 | 4.8 MB | ||
| 10. Query Tools and Steps.vtt | 4.1 KB | ||
| 2. Demo - Conditional Pipeline Flow.mp4 | 12.8 MB | ||
| 2. Demo - Conditional Pipeline Flow.vtt | 7.4 KB | ||
| 2. Demo - Eventhouse Monitoring.mp4 | 17 MB | ||
| 2. Demo - Eventhouse Monitoring.vtt | 7.1 KB | ||
| 2. Demo - Monitor Hub.mp4 | 20 MB | ||
| 2. Demo - Monitor Hub.vtt | 8 KB | ||
| 3. Demo - Send Email Failure.mp4 | 14.1 MB | ||
| 3. Demo - Send Email Failure.vtt | 6.8 KB | ||
| 3. Eventstream Errors.mp4 | 8.2 MB | ||
| 3. Eventstream Errors.vtt | 7.2 KB | ||
| 3. Logging.mp4 | 2.8 MB | ||
| 3. Logging.vtt | 2.2 KB | ||
| 4. Dataflow Issues.mp4 | 6.2 MB | ||
| 4. Dataflow Issues.vtt | 4.5 KB | ||
| 4. Demo - Event Stream Schema Change.mp4 | 11 MB | ||
| 4. Demo - Event Stream Schema Change.vtt | 5 KB | ||
| 4. Demo - Logging.mp4 | 17.9 MB | ||
| 4. Demo - Logging.vtt | 5.6 KB | ||
| 5. Demo - Dataflow Errors.mp4 | 12.5 MB | ||
| 5. Demo - Dataflow Errors.vtt | 5.2 KB | ||
| 5. Demo - Monitoring Semantic Models.mp4 | 21 MB | ||
| 5. Demo - Monitoring Semantic Models.vtt | 8.4 KB | ||
| 5. Warehouse Queries.mp4 | 9.3 MB | ||
| 5. Warehouse Queries.vtt | 8.4 KB | ||
| 6. Demo - Warehouse Constraint Issues.mp4 | 14.5 MB | ||
| 6. Demo - Warehouse Constraint Issues.vtt | 5.6 KB | ||
| 6. Notebook Best Practices.mp4 | 4.2 MB | ||
| 6. Notebook Best Practices.vtt | 3.5 KB | ||
| 7. Demo - Notebook Errors.mp4 | 18.2 MB | ||
| 7. Demo - Notebook Errors.vtt | 6.5 KB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| playlist.m3u | 2.2 KB | ||
| ▲ 59 total files | |||
Microsoft Fabric Data Engineer (DP-700): Monitor and Optimize an Analytics Solution
https://WebToolTip.com
Released 7/2025
By Thomas LeBlanc
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Advanced | Genre: eLearning | Language: English + subtitle | Duration: 1h 47m | Size: 320 MB
This course will teach you how to monitor for issues, debug code, and optimize storage and compute resources implemented in Microsoft Fabric.
Performance-tuning a deployed Fabric implementation needs proper monitoring for patterns and conditions to assist in an optimal data system. Debugging errors and identifying non-optimized structures can lead to a healthier lakehouse system. In this course, Microsoft Fabric Data Engineer (DP-700): Monitor and Optimize an Analytics Solution, you’ll gain the ability to use performance monitoring tools to diagnose errors and resolve issues improving the overall performance. First, you’ll explore monitoring tools for data ingestions, curating various data sources for a gold semantic layer and using alerts to proactively find issues. Next, you’ll discover errors in pipelines and data flows while debugging the code. Then, you'll examine tips for common errors in streaming and warehouse data that are using KQL or T-SQL. Finally, you’ll learn how to optimize performance in a lakehouse for delta tables, use the spark engine in notebooks, and improve eventstreams and eventhouses for near-real-time data. When you’re finished with this course, you’ll have the skills and knowledge of Microsoft Fabric data engineering needed to pass the DP-700 exam section for monitoring, fixing errors and optimization.
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