Data Warehousing Training

Industry-designed combo training course that includes the Microsoft Business Intelligence tool and its components like SSRS, SSIS, and SSAS that use the SQL Server. This training will provide you with full proficiency in working with MSBI, ETL tasks, analytics, data integration, and reporting.

 Data Warehousing Training

Data Warehousing Training

Our Data Warehousing Training program lets you gain proficiency in Microsoft Business Intelligence and crystal clear concepts of Data Warehousing. You will work on real-world industry projects pertaining to the three components of MSBI, SSIS for ETL, SSAS for analysis, and SSRS for reporting along with data mining queries, Visual Studio, SQL Server, Data quality ,using master Data Services and Implementing an Azure sql Data Warehouse. As part of this training from TrainingHub.io, you will also receive the official course material issued by Microsoft all topics.

 Data Warehousing Training

Student Journey


After this course of Data Warehousing Training course what traininghub.io offering students will gain in Depth Knowledge of DW Concepts including ETL and Multidimensional Modelling Data modeling, planning data warehouse infrastructure transformation, designing and implementing data warehousing ,columstore indexes , explore and implement ETL solution. Also students will learn SSIS in very detail which is used industry wide , enforcing data Quality (DQ) , using Master Data Services ,implementing Azure SQL data warehouse ,reporting tool SSRS in detail and PowerBI

 Data Warehousing Training- Student Journey
 Data Warehousing Training- Student Journey

Course Content


  • Introduction to Data Warehousing
    • Overview of Data Warehousing
    • Considerations for a Data Warehouse Solution
    • Lab: Exploring a Data Warehouse Solution
  • Dimension Modeling & Data Ware Housing
    • Dimension Modeling & Data Ware Housing
    • Basic concepts of Business Intelligence
    • Basic concepts of Data Warehousing
    • Designing facts and dimensions
    • Employing key performance indicators
    • Dimensional modeling process to design Data Warehouse
  • Planning Data Warehouse Infrastructure
    • Considerations for Building a Data Warehouse
    • Data Warehouse Reference Architectures and Appliances
    • Lab: Planning Data Warehouse Infrastructure
  • Designing and Implementing a Data Warehouse
    • Logical Design for a Data Warehouse
    • Physical Design for a Data Warehouse
    • Lab: Implementing a Data Warehouse Schema
  • Columnstore Indexes
    • Introduction to Columnstore Indexes
    • Creating Columnstore Indexes
    • Working with Columnstore Indexes
    • Lab: Using Columnstore Indexes
  • Creating an ETL Solution
    • Introduction to ETL with SSIS
    • Exploring Source Data
    • Implementing Data Flow
    • Lab: Implementing Data Flow in an SSIS Package
  • Implementing Control Flow in an SSIS Package
    • Introduction to Control Flow
    • Creating Dynamic Packages
    • Introduction to Control Flow
    • Using Containers
    • Lab: Implementing Control Flow in an SSIS Package and Lab: Using Transactions and Checkpoints/li>
  • Debugging and Troubleshooting SSIS Packages
    • Debugging an SSIS Package
    • Logging SSIS Package Events
    • Handling Errors in an SSIS Package
    • Lab: Debugging and Troubleshooting an SSIS Package
  • Implementing an Incremental ETL Process
    • Introduction to Incremental ETL
    • Extracting Modified Data
    • Temporal Tables
    • Lab: Extracting Modified DataLab: Loading Incremental Changes
  • Extending SQL Server Integration Services (SSIS)
    • Using Custom Components in SSIS
    • Using Scripting in SSIS
    • Lab: Using Scripts and Custom Components
  • Deploying and Configuring SSIS Packages
    • Overview of SSIS Deployment
    • Deploying SSIS Projects
    • Planning SSIS Package Execution
    • Lab: Deploying and Configuring SSIS Packages
  • Enforcing Data Quality
    • Introduction to Data Quality
    • Using Data Quality Services to Cleanse Data
    • Using Data Quality Services to Match Data
    • Lab: Cleansing DataLab: De-duplicating Data
  • Consuming Data in a Data Warehouse
    • Introduction to Business Intelligence
    • Introduction to Reporting
    • An Introduction to Data Analysis
    • Analyzing Data with Azure SQL Data Warehouse
    • Lab: Using Business Intelligence Tools
  • Using Master Data Services
    • Master Data Services Concepts
    • Implementing a Master Data Services Model
    • Managing Master Data
    • Creating a Master Data Hub
    • Lab: Implementing Master Data Services
  • Implementing an Azure SQL Data Warehouse
    • Implementing an Azure SQL Data Warehouse
    • Advantages of Azure SQL Data Warehouse
    • Developing an Azure SQL Data Warehouse
    • Migrating to an Azure SQ Data Warehouse
    • Lab: Implementing an Azure SQL Data Warehouse
  • MS SQL Server Reporting Services (SSRS)
    • Producing table and matrix report with drill down and drill through functionality
    • Produce reports with enhanced visualization features such as charts, map and gauge
    • Integrate parameters, filters and interactive components into reports
    • Create reports on SSAS cubes with Report Builder
    • Deploying reports to the Report Server
    • Creating cached instances, snapshots and subscriptions
    • Configuring and testing security on report items
    • Report performance tuning
  • Power BI
    • Perform Power BI desktop data transformation
    • Describe Power BI desktop modelling
    • Create a Power BI desktop visualization
    • Implement the Power BI service
    • Describe how to connect to Excel data
    • Describe how to collaborate with Power BI data
    • Connect directly to data stores