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20767 MOD: Implementing a SQL Data Warehouse
About this On Demand Course
The Microsoft on-demand product is an integrated on-line training experience that includes video, labs, exercises, text and knowledge checks. Attendees experience all of this through an on-demand course player.
- Access to the official Microsoft Video on Demand Course for 90 days from the point of first access, allowing you to start and stop when you need to.
- Lab access for 3 months from start of access.
- Digital edition of the Microsoft Official Curriculum (DMOC) manual for reference throughout your course. All DMOC come with fresh editions so your courseware will always be up to date.
- Mentoring Support (24/7 by chat, email or phone) for the duration of your subscription
The content is based on the same official courseware we use in our instructor-led training, and videos feature engaging experts hand-selected by Microsoft. Unlike other on-demand offerings that offer simulated labs, MOC On-Demand gives you a live, real-time environment for hands-on training.
About this course
This course provides students with the knowledge and skills to provision a Microsoft SQL Server 2016 database. The course covers SQL Server 2016 provision both on-premise and in Azure, and covers installing from new and migrating from an existing install.
In addition to their professional experience, students who attend this training should already have the following technical knowledge:
- Basic knowledge of the Microsoft Windows operating system and its core functionality.
- Working knowledge of relational databases.
- Some experience with database design.
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:
Provision a Database Server.
Upgrade SQL Server.
Configure SQL Server.
Manage Databases and Files (shared).
Module 1: Introduction to Data Warehousing
This module describes data warehouse concepts and architecture consideration.
Overview of Data Warehousing
Considerations for a Data Warehouse Solution
Lab: Exploring a Data Warehouse Solution
Exploring data sources
Exploring an ETL process
Exploring a data warehouse
Module 2: Planning Data Warehouse Infrastructure
This module describes the main hardware considerations for building a data warehouse.
Considerations for data warehouse infrastructure.
Planning data warehouse hardware.
Lab: Planning Data Warehouse Infrastructure
Planning data warehouse hardware
Module 3: Designing and Implementing a Data Warehouse
This module describes how you go about designing and implementing a schema for a data warehouse.
Designing dimension tables
Designing fact tables
Physical Design for a Data Warehouse
Lab: Implementing a Data Warehouse Schema
Implementing a star schema
Implementing a snowflake schema
Implementing a time dimension table
Module 4: Columnstore Indexes
This module introduces Columnstore Indexes.
Introduction to Columnstore Indexes
Creating Columnstore Indexes
Working with Columnstore Indexes
Lab: Using Columnstore Indexes
Create a Columnstore index on the FactProductInventory table
Create a Columnstore index on the FactInternetSales table
Create a memory optimized Columnstore table
Module 5: Implementing an Azure SQL Data Warehouse
This module describes Azure SQL Data Warehouses and how to implement them.
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
Copying data with the Azure data factory
Lab: Implementing an Azure SQL Data Warehouse
Create an Azure SQL data warehouse database
Migrate to an Azure SQL Data warehouse database
Copy data with the Azure data factory
Module 6: Creating an ETL Solution
At the end of this module you will be able to implement data flow in a SSIS package.
Introduction to ETL with SSIS
Exploring Source Data
Implementing Data Flow
Lab: Implementing Data Flow in an SSIS Package
Exploring source data
Transferring data by using a data row task
Using transformation components in a data row
Module 7: Implementing Control Flow in an SSIS Package
This module describes implementing control flow in an SSIS package.
Introduction to Control Flow
Creating Dynamic Packages
Lab: Implementing Control Flow in an SSIS Package
Using tasks and precedence in a control flow
Using variables and parameters
Lab: Using Transactions and Checkpoints
Module 8: Debugging and Troubleshooting SSIS Packages
This module describes how to debug and troubleshoot SSIS packages.
Debugging an SSIS Package
Logging SSIS Package Events
Handling Errors in an SSIS Package
Lab: Debugging and Troubleshooting an SSIS Package
Debugging an SSIS package
Logging SSIS package execution
Implementing an event handler
Handling errors in data flow
Module 9: Implementing a Data Extraction Solution
This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.
Introduction to Incremental ETL
Extracting Modified Data
Loading modified data
Lab: Extracting Modified Data
Using a datetime column to incrementally extract data
Using change data capture
Using the CDC control task
Using change tracking
Lab: Loading a data warehouse
Loading data from CDC output tables
Using a lookup transformation to insert or update dimension data
Implementing a slowly changing dimension
Using the merge statement
Module 10: Enforcing Data Quality
This module describes how to implement data cleansing by using
Microsoft Data Quality services.
Introduction to Data Quality
Using Data Quality Services to Cleanse Data
Using Data Quality Services to Match Data
Lab: Cleansing Data
Creating a DQS knowledge base
Using a DQS project to cleanse data
Using DQS in an SSIS package
Lab: De-duplicating Data
Creating a matching policy
Using a DS project to match data
Module 11: Using Master Data Services
This module describes how to implement master data services to enforce data integrity at source.
Introduction to Master Data Services
Implementing a Master Data Services Model
Hierarchies and collections
Creating a Master Data Hub
Lab: Implementing Master Data Services
Creating a master data services model
Using the master data services add-in for Excel
Enforcing business rules
Loading data into a model
Consuming master data services data
Module 12: Extending SQL Server Integration Services (SSIS)
This module describes how to extend SSIS with custom scripts and components.
Using scripting in SSIS
Using custom components in SSIS
Lab: Using scripts
Using a script task
Module 13: Deploying and Configuring SSIS Packages
This module describes how to deploy and configure SSIS packages.
Overview of SSIS Deployment
Deploying SSIS Projects
Planning SSIS Package Execution
Lab: Deploying and Configuring SSIS Packages
Creating an SSIS catalog
Deploying an SSIS project
Creating environments for an SSIS solution
Running an SSIS package in SQL server management studio
Scheduling SSIS packages with SQL server agent
Module 14: Consuming Data in a Data Warehouse
This module describes how to debug and troubleshoot SSIS packages.
Introduction to Business Intelligence
An Introduction to Data Analysis
Introduction to reporting
Analyzing Data with Azure SQL Data Warehouse
Lab: Using a data warehouse
Exploring a reporting services report
Exploring a PowerPivot workbook
Exploring a power view report