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FormateurAlaa Hady MBA, AI Engineer
Associé gérant, Advanced Management Solutions
Instructor: Alaa Hady · Language: English or Arabic · Suggested duration: 3–4 days · Level: Advanced (Level 300)
Objectives
- Plan and execute seamless enterprise migrations from legacy data platforms (Azure Synapse Analytics, ADF, Databricks, Snowflake, SSRS/On-Prem SQL) to Microsoft Fabric.
- Engineer production-grade hybrid batch and streaming data pipelines using PySpark, T-SQL, KQL, and Eventstreams.
- Implement automated CI/CD, observability, data quality frameworks (Great Expectations /
sempy), and error recovery. - Optimize Spark and Warehouse compute performance across massive enterprise volumes.
Outline and contents
- Assessing legacy architectures and building a phased Fabric Migration Roadmap
- Migrating Azure Synapse Dedicated & Serverless SQL Pools and On-Prem SQL Server DWs to Fabric Data Warehouse
- Migrating Azure Data Factory (ADF) and SSIS packages to Fabric Data Factory Pipelines and Dataflows Gen2
- Coexistence and integration patterns with Azure Databricks and Snowflake (OneLake Shortcuts, Iceberg/Delta XTable interoperability & Database Mirroring)
- Advanced PySpark & Delta Lake engineering: Structured Streaming, Change Data Feed (CDF), Liquid Clustering, and handling schema drift
- Handling PII data masking, hashing, and row/column security during ingestion
- Enterprise observability: Spark UI diagnostics, skew/shuffle tuning, Warehouse Query Insights, and automated data quality checks
- CI/CD automation using Git, Variable Libraries, and Fabric REST APIs
- Hands-on Migration & Engineering Lab
Target audience
Data engineers, cloud architects, Synapse/ADF/Databricks developers, and technical leads planning or executing enterprise migrations to Fabric.
Expected outcomes
Participants master advanced multi-engine data engineering in Fabric and gain actionable migration blueprints from legacy data platforms. (Note: Learners seeking dedicated exam preparation for Microsoft Exam DP-700 should also see Course 47 in Academy G).
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