About this course
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.
Audience profile
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.
At course completion
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
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
Auditoriniai mokymai
| Pradžios data | Trukmė, d. | Kurso pavadinimas | Kaina, € | Statusas |
| Užklausti | 5 | 20761: Querying Data with Transact-SQL | 1500 | Organizuojamas |
| Užklausti | 5 | 20764: Administering a SQL Database Infrastructure | 1500 | Organizuojamas |
| Užklausti | 5 | 20767: Implementing a SQL Data Warehouse | 1500 | Organizuojamas |
| Užklausti | 4 | 10987: Performance Tuning and Optimizing SQL Databases | 1400 | Organizuojamas |
| Užklausti | 5 | 20762: Developing SQL Databases | 1500 | Organizuojamas |
| Užklausti | 5 | 20765: Provisioning SQL Databases | 1500 | Organizuojamas |
| Užklausti | 3 | 10988: Managing SQL Business Intelligence Operations | 1200 | Organizuojamas |
| Užklausti | 3 | 20768: Developing SQL Data Models | 1200 | Organizuojamas |
| Užklausti | 3 | 10989: Analyzing Data with Power BI | 1200 | Organizuojamas |
| Užklausti | 5 | 10990: Analyzing Data with SQL Server Reporting Services | 1500 | Organizuojamas |