Classes Microsoft Technical
20767C Microsoft Partner Delivered
Implementing a SQL Data Warehouse – SSIS
- 4 days
- 4 upcoming dates
Upcoming dates
All times shown in the class's own timezone. Dates we teach ourselves run once 1 people are booked, so a pair of seats confirms one.
| Dates | Starts | Where | Status | Seat | Book |
|---|---|---|---|---|---|
| Nov 3-6 | 6:00 AM to 2:00 PM PST Partner Delivered | Live virtual | RUNS WITH 1+ | $2,995 | |
| Dec 1-4 | 6:00 AM to 2:00 PM PST Partner Delivered | Live virtual | RUNS WITH 1+ | $2,995 | |
| Feb 9-12 | 6:00 AM to 2:00 PM PST Partner Delivered | Live virtual | RUNS WITH 1+ | $2,995 | |
| Mar 16-19 | 6:00 AM to 2:00 PM PDT Partner Delivered | Live virtual | RUNS WITH 1+ | $2,995 |
About this class
We have 4 scheduled dates of Implementing a SQL Data Warehouse – SSIS, from Nov 3-6 through Mar 16-19. Seats are $2,995 each over 4 days, courseware included. Book online with a card, or send a purchase order and we will invoice on net 30 terms.
This five-day instructor-led course provides students with the knowledge and skills to provision a Microsoft SQL Server 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. 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.
What you'll be able to do
- 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
Course outline
Module 1 Introduction to Data Warehousing
- 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 After completing this module, you will be able to:
- Describe the key elements of a data warehousing solution
- Describe the key considerations for a data warehousing solution
Module 2 Planning Data Warehouse Infrastructure
- Considerations for Building a Data Warehouse
- Planning data warehouse hardware Lab : Planning Data Warehouse Infrastructure
- Planning data warehouse hardware After completing this module, you will be able to:
- Describe the main hardware considerations for building a data warehouse
- Explain how to use reference architectures and data warehouse appliances to create a data warehouse
Module 3 Designing and Implementing a Data Warehouse
- Data warehouse design overview
- 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 After completing this module, you will be able to:
- Implement a logical design for a data warehouse
- Implement a physical design for a data warehouse
Module 4 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 After completing this module, you will be able to:
- Create Columnstore indexes
- Work with Columnstore Indexes
Module 5 Implementing an Azure SQL Data Warehouse
- 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 After completing this module, you will be able to:
- Describe the advantages of Azure SQL Data Warehouse
- Implement an Azure SQL Data Warehouse
- Describe the considerations for developing an Azure SQL Data Warehouse
- Plan for migrating to Azure SQL Data Warehouse
Module 6 Creating an ETL Solution
- 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 After completing this module, you will be able to:
- Describe ETL with SSIS
- Explore Source Data
- Implement a Data Flow
Module 7 Implementing Control Flow in an SSIS Package
- Introduction to Control Flow
- Creating Dynamic Packages
- Using Containers
- Managing consistency Lab : Implementing Control Flow in an SSIS Package
- Using tasks and precedence in a control flow
- Using variables and parameters
- Using containers Lab : Using Transactions and Checkpoints
- Using transactions
- Using checkpoints After completing this module, you will be able to:
- Describe control flow
- Create dynamic packages
- Use containers
Module 8 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
- Debugging an SSIS package
- Logging SSIS package execution
- Implementing an event handler
- Handling errors in data flow After completing this module, you will be able to:
- Debug an SSIS package
- Log SSIS package events
- Handle errors in an SSIS package
Module 9 Implementing a Data Extraction Solution
- Introduction to Incremental ETL
- Extracting Modified Data
- Loading modified data
- Temporal Tables Lab : Extracting Modified Data
- Using a datetime column to incrementally extract data
- Using change data capture
- Using the CDC control task
- Using change tracking
- 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 After completing this module, you will be able to:
- Describe incremental ETL
- Extract modified data
- Describe temporal tables
Module 10 Enforcing Data Quality
- 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 After completing this module, you will be able to:
- Describe data quality services
- Cleanse data using data quality services
- Match data using data quality services
- De-duplicate data using data quality services
Module 11 Using Master Data Services
- 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 After completing this module, you will be able to:
- Describe the key concepts of master data services
- Implement a master data service model
- Manage master data
- Create a master data hub
Module 12 Extending SQL Server Integration Services (SSIS)
- Using Custom Components in SSIS
- Using Scripting in SSIS Lab : Using Scripts
- Using a script task After completing this module, you will be able to:
- Use custom components in SSIS
- Use scripting in SSIS
Module 13 Deploying and Configuring 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 After completing this module, you will be able to:
- Describe an SSIS deployment
- Deploy an SSIS package
- Plan SSIS package execution
Module 14 Consuming Data in a Data Warehouse
- 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 After completing this module, you will be able to:
- Describe at a high level business intelligence
- Show an understanding of reporting
- Show an understanding of data analysis
- Analyze data with Azure SQL data warehouse
Before you attend
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.
How reserving works. Your card is authorized, not charged. We confirm the seat with the training center, usually within one business day, and take payment only once it is held. If the class turns out to be full we release the authorization and you are not charged.
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