Intermediate3 days
Azure Synapse Analytics
Unified data warehousing and big data at enterprise scale
Overview
Azure Synapse Analytics brings together enterprise data warehousing and big data analytics. This training covers dedicated and serverless SQL pools, Spark integration, Synapse Pipelines, and best practices for building scalable, cost-efficient analytical workloads on Azure.
What you'll learn
- Design and provision a Synapse Analytics workspace
- Build data pipelines using Synapse Pipelines and mapping data flows
- Query data at scale with dedicated SQL pools and serverless SQL
- Process big data with Apache Spark pools in Synapse
- Integrate Synapse with Azure Data Lake Storage Gen2
- Monitor costs, performance, and workload management
Programme
Day 1 — Workspace setup & SQL analytics
- Synapse Analytics architecture overview
- Creating and configuring a Synapse workspace
- Dedicated SQL pool: provisioning, distribution strategies, and indexing
- Serverless SQL pool: querying data lake files without infrastructure
- PolyBase and COPY INTO for high-throughput data loading
- Hands-on: load and query a star schema in dedicated SQL pool
Day 2 — Spark and data engineering
- Apache Spark in Synapse: pools, runtimes, and libraries
- Processing structured and unstructured data with PySpark
- Delta Lake integration: ACID transactions on your data lake
- Synapse Pipelines: orchestrating complex ETL workflows
- Mapping Data Flows: visual ETL at scale
- Hands-on: build a PySpark transformation job with Delta output
Day 3 — Integration, governance & optimisation
- Connecting Synapse to Power BI, Azure ML, and Purview
- Row-level security and column encryption
- Workload management and query performance tuning
- Cost management: pausing, scaling, and right-sizing pools
- Monitoring with Synapse Studio and Azure Monitor
- Hands-on: performance-tune a slow analytical query end to end
Who is this for?
- Data engineers designing cloud-native analytical platforms
- SQL developers moving to massively parallel processing workloads
- Solution architects evaluating Azure data platform options
- Teams migrating from on-premises data warehouses to Azure
Prerequisites
- Solid understanding of SQL and data warehousing concepts
- Basic Azure familiarity (portal navigation, resource groups)
- Python or Scala experience helpful for Spark modules
Tools & technologies covered
Azure Synapse AnalyticsDedicated SQL PoolServerless SQLApache SparkDelta LakeAzure Data Lake Storage Gen2Power BI
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