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Course Outline

Module 1: Modern Data Warehousing & Business Intelligence Fundamentals:

  • Evolving Landscape of Data Warehousing (DW) and Business Intelligence (BI)
  • Cloud-Native Data Warehousing (Azure Synapse Analytics, Azure SQL Data Warehouse)
  • Modern Data Warehouse Architectures (Lambda Architecture, Kappa Architecture)
  • Data Modeling Concepts (Star Schema, Snowflake Schema)
  • Introduction to Data Vault methodology (brief overview)
  • Key BI Concepts: ETL/ELT, OLAP, OLAP, DWH, Data Governance
  • Overview of the Microsoft BI Stack: SQL Server (T-SQL, SSIS, SSAS, SSRS), Azure Synapse Analytics, Azure Analysis Services, Azure Data Factory, Power BI

Module 2: Modern ETL/ELT with SQL Server Integration Services (SSIS)

  • SSIS Core Components (Integration Services, Connection Managers, Data Flow, Control Flow)
  • Modern Data Access (ADO.NET, OLE DB, ODBC, Python Script Task)
  • Cloud Integration (Loading/unloading data from/to Azure Blob Storage, Azure SQL Database/DW, Azure Data Lake Storage Gen2)
  • Data Transformation Techniques (Derived Column, Lookup transformations, Aggregate transformations, Conditional Split, Script Component)
  • Handling Big Data in SSIS (Integration with Azure Databricks, PolyBase)
  • Error Handling, Logging, and Debugging in SSIS
  • Deployment and Scheduling (SQL Agent, Azure Automation Runbooks)

Module 3: Building Analytical Models with SQL Server Analysis Services (SSAS - Tabular)

  • Introduction to the Tabular Model (vs Multidimensional)
  • DAX (Data Analysis Expressions) Language Fundamentals (Context, Calculations, Aggregations)
  • Model Design: Relationships, Hierarchies, Perspectives, Roles, Security
  • Using Time Intelligence Functions in DAX
  • Managing and Deploying Tabular Models (BIML, SSDT)
  • Performance Tuning SSAS Tabular Models

Module 4: Cloud Analytics with Azure Analysis Services (AAS)

  • Introduction to Azure Analysis Services (AAS)
  • AAS Deployment Options (PaaS - Azure App Service Plan, Dedicated Compute Instance)
  • Connecting to Azure Databases (Azure Synapse Analytics, Azure SQL Database, Azure Analysis Services)
  • Model Authoring in Azure (using Azure Purview or Azure Analysis Services Studio)
  • Scaling and High Availability with AAS
  • Security in AAS (Role-Based Security)

Module 5: Querying and Analyzing Data with T-SQL and DAX

  • Advanced T-SQL for Data Analysis (CTEs, Window Functions, PIVOT/UNPIVOT, MERGE)
  • DAX Deep Dive (Row Context vs Filter Context, Iterators, Time Intelligence, KPIs, Q&A)
  • Combining T-SQL and DAX (PolyBase queries, linked servers)
  • Using AI-Enhanced Analytics (Azure Synapse Analytics Machine Learning Services)

Module 6: Data Discovery and Visualization

  • Introduction to Power BI (Connecting to Data Sources, Query Editor)
  • Creating Effective Visualizations (Charts, Graphs, Maps)
  • DAX for Power BI (Calculated Columns, Measures)
  • Report Design and Formatting in Power BI
  • Introduction to Azure Synapse Studio for BI

Module 7: Course Review, Advanced Concepts & Hands-on Labs

  • Advanced Data Transformation Patterns (Slowly Changing Dimensions, Type 1/2)
  • Data Quality Services (DQS) Integration (overview)
  • Performance Optimization and Troubleshooting (Query Store, Execution Plans)
  • Extending BI Capabilities (Power Query, Power Automate)
  • Hands-on labs covering end-to-end BI scenarios (ETL, Model Building, Reporting)

Requirements

Knowledge of Windows, basic knowledge of SQL and relational databases.

 14 Hours

Custom Corporate Training

Training solutions designed exclusively for businesses.

  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

Price per private group, online live training, starting from 3200 € + VAT*

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