Implementing a SQL Data Warehouse Training in Sweden

  • Learn via: Classroom / Virtual Classroom / Online
  • Duration: 5 Days
  • Price: Please contact for booking options
We can host this training at your preferred location. Contact us!

This 5 day instructor led course describes how to implement a data warehouse platform to support a BI solution. Students will learn how to create a data warehouse with Microsoft® SQL Server® 2016 and with Azure SQL Data Warehouse, to implement ETL with SQL Server Integration Services, and to validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.

Target Audience

The primary audience for this course are database professionals who need to fulfil a Business Intelligence Developer role. They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing.

This course requires that you meet the following prerequisites:

  • Basic knowledge of the Microsoft Windows operating system and its core functionality.
  • Working knowledge of relational databases.
  • Some experience with database design

After completing this course, students will be able to:

  • Describe the key elements of a data warehousing solution
  • Describe the main hardware considerations for building a data warehouse
  • Implement a logical design for a data warehouse
  • Implement a physical design for a data warehouse
  • Create columnstore indexes
  • Implementing an Azure SQL Data Warehouse
  • Describe the key features of SSIS
  • Implement a data flow by using SSIS
  • Implement control flow by using tasks and precedence constraints
  • Create dynamic packages that include variables and parameters
  • Debug SSIS packages
  • Describe the considerations for implement an ETL solution
  • Implement Data Quality Services
  • Implement a Master Data Services model
  • Describe how you can use custom components to extend SSIS
  • Deploy SSIS projects
  • Describe BI and common BI scenarios

Module 1: Introduction to Data Warehousing

Describe data warehouse concepts and architecture considerations.

Lessons

  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution


Lab : Exploring a Data Warehouse Solution

Module 2: Planning Data Warehouse Infrastructure

This module describes the main hardware considerations for building a data warehouse.

Lessons

  • Considerations for Building a Data Warehouse
  • Data Warehouse Reference Architectures and Appliances


Lab : Planning Data Warehouse Infrastructure

Module 3: Designing and Implementing a Data Warehouse

This module describes how you go about designing and implementing a schema for a data warehouse.

Lessons

  • Logical Design for a Data Warehouse
  • Physical Design for a Data Warehouse


Lab : Implementing a Data Warehouse Schema

Module 4: Columnstore Indexes

This module introduces Columnstore Indexes.

Lessons

  • Introduction to Columnstore Indexes
  • Creating Columnstore Indexes
  • Working with Columnstore Indexes


Lab : Using Columnstore Indexes

Module 5: Implementing an Azure SQL Data Warehouse

This module describes Azure SQL Data Warehouses and how to implement them.

Lessons

  • Advantages of Azure SQL Data Warehouse
  • Implementing an Azure SQL Data Warehouse
  • Developing an Azure SQL Data Warehouse
  • Migrating to an Azure SQ Data Warehouse


Lab : Implementing an Azure SQL Data Warehouse

Module 6: Creating an ETL Solution

At the end of this module you will be able to implement data flow in a SSIS package.

Lessons

  • Introduction to ETL with SSIS
  • Exploring Source Data
  • Implementing Data Flow


Lab : Implementing Data Flow in an SSIS Package

Module 7: Implementing Control Flow in an SSIS Package

This module describes implementing control flow in an SSIS package.

Lessons

  • Introduction to Control Flow
  • Creating Dynamic Packages
  • Using Containers


Lab : Implementing Control Flow in an SSIS PackageLab : Using Transactions and Checkpoints

Module 8: Debugging and Troubleshooting SSIS Packages

This module describes how to debug and troubleshoot SSIS packages.

Lessons

  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in an SSIS Package


Lab : Debugging and Troubleshooting an SSIS Package

Module 9: Implementing an Incremental ETL Process

This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.

Lessons

  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Temporal Tables


Lab : Extracting Modified DataLab : Loading Incremental Changes

Module 10: Enforcing Data Quality

This module describes how to implement data cleansing by using Microsoft Data Quality services.

Lessons

  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match Data


Lab : Cleansing DataLab : De-duplicating Data

Module 11: Using Master Data Services

This module describes how to implement master data services to enforce data integrity at source.

Lessons

  • Master Data Services Concepts
  • Implementing a Master Data Services Model
  • Managing Master Data
  • Creating a Master Data Hub


Lab : Implementing Master Data Services

Module 12: Extending SQL Server Integration Services (SSIS)

This module describes how to extend SSIS with custom scripts and components.

Lessons

  • Using Custom Components in SSIS
  • Using Scripting in SSIS


Lab : Using Scripts and Custom Components

Module 13: Deploying and Configuring SSIS Packages

This module describes how to deploy and configure SSIS packages.

Lessons

  • Overview of SSIS Deployment
  • Deploying SSIS Projects
  • Planning SSIS Package Execution


Lab : Deploying and Configuring SSIS Packages

Module 14: Consuming Data in a Data Warehouse

This module describes how to debug and troubleshoot SSIS packages.

Lessons

  • Introduction to Business Intelligence
  • Introduction to Reporting
  • An Introduction to Data Analysis
  • Analyzing Data with Azure SQL Data Warehouse


Lab : Using Business Intelligence Tools



Contact us for more detail about our trainings and for all other enquiries!

Upcoming Trainings

Join our public courses in our Sweden facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom
26 skábmamánnu 2024
Stockholm, Malmö, Göteborg
5 Days
Classroom / Virtual Classroom
26 skábmamánnu 2024
Stockholm, Malmö, Göteborg
5 Days
Classroom / Virtual Classroom
27 ođđajagemánnu 2025
Stockholm, Malmö, Göteborg
5 Days
Classroom / Virtual Classroom
22 guovvamánnu 2025
Stockholm, Malmö, Göteborg
5 Days
Classroom / Virtual Classroom
27 ođđajagemánnu 2025
Stockholm, Malmö, Göteborg
5 Days
Classroom / Virtual Classroom
23 guovvamánnu 2025
Stockholm, Malmö, Göteborg
5 Days
Classroom / Virtual Classroom
27 guovvamánnu 2025
Stockholm, Malmö, Göteborg
5 Days
Classroom / Virtual Classroom
22 guovvamánnu 2025
Stockholm, Malmö, Göteborg
5 Days
Implementing a SQL Data Warehouse Training Course in Sweden

Sweden is a Nordic country that borders Norway, Finland and Denmark. The name "Sweden" originated from the "Svear", a people mentioned by the Roman author Tacitus. While being the largest Nordic country, Sweden is the fifth-largest country in Europe. Sweden has a total population of 10.4 million. The capital and largest city is Stockholm. About 15 percent of the country lies within the Arctic Circle, so that's why from May until mid-July, sunlight lasts all day in the north of the Arctic Circle. On the other hand, during December, the capital citt experiences only about 5.5 hours of daylight.

When in Sweden, visiting Stockholm's Old Town Gamla Stan, Sweden's most popular museum Vasa Museum and a UNESCO World Heritage Site; Drottningholm Palace is highly recommended.

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