Implementing a Data Warehouse with Microsoft SQL Server 2012 Training (M10777)
Implementing a Data Warehouse with Microsoft SQL Server 2012 Training Course Description
Data warehousing is a solution organizations use to centralize business data for reporting and analysis. This five-day instructor-led Implementing a Data Warehouse with Microsoft SQL Server 2012 Training course focuses on teaching individuals how to create a data warehouse with SQL Server 2012, implement ETL with SQL Server Integration Services, and validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services. This Implementing a Data Warehouse with Microsoft SQL Server 2012 Training course helps people prepare for exam 70-463.
With onsite Training, courses can be scheduled on a date that is convenient for you, and because they can be scheduled at your location, you don’t incur travel costs and students won’t be away from home. Onsite classes can also be tailored to meet your needs. You might shorten a 5-day class into a 3-day class, or combine portions of several related courses into a single course, or have the instructor vary the emphasis of topics depending on your staff’s and site’s requirements.
Implementing a data warehouse.
Developing SQL Server Integration Services (SSIS) packages for data extraction, transformation, and loading (ETL).
Enforcing data integrity by using Master Data Services.
Cleansing data by using Data Quality Services
Duration: 5 days
What You Will Learn:
Describe data warehouse concepts and architecture considerations.
Select an appropriate hardware platform for a data warehouse.
Design and implement a data warehouse.
Implement Data Flow in an SSIS Package.
Implement Control Flow in an SSIS Package.
Debug and Troubleshoot SSIS packages.
Implement an SSIS solution that supports incremental data warehouse loads and changing data.
Integrate cloud data into a data warehouse ecosystem infrastructure.
Implement data cleansing by using Microsoft Data Quality Services.
Implement Master Data Services to enforce data integrity.
Extend SSIS with custom scripts and components.
Deploy and Configure SSIS packages.
Describe how information workers can consume data from the data warehouse
Module 1: Introduction to Data Warehousing
Overview of Data Warehousing
Considerations for a Data Warehouse Solution
Lab: Exploring a Data Warehousing Solution
Exploring data sources
Exploring an ETL solution
Exploring a data warehouse
Module 2: Data Warehouse Hardware
Considerations for Building a Data Warehouse
Data Warehouse Reference Architectures and Appliances
Module 3: Designing and Implementing a Data Warehouse
Logical Design for a Data Warehouse
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: Creating an ETL Solution with SSIS
Introduction to ETL with SSIS
Exploring Source Data
Implementing Data Flow
Lab: Implementing Data Flow in a SSIS Package
Exploring Source Data
Transferring Data by Using a Data Flow Task
Using Transformations in a Data Flow
Module 5: 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 6: 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 a Data Flow
Module 7: Implementing an Incremental ETL Process
Introduction to Incremental ETL
Extracting Modified Data
Loading Modified Data
Lab: Extracting Modified Data
Using a DateTime Column to Incrementally Extract Data
Using a Change Data Capture
Using Change Tracking
Lab: Loading Incremental Changes
Using a Lookup Transformation to Insert Dimension Data
Using a Lookup Transformation to Insert or Update Dimension Data
Implementing a Slowly Changing Dimension
Using a MERGE Statement to Load Fact Data
Module 8: Incorporating Data from the Cloud into a Data Warehouse
Overview of Cloud Data Sources
SQL Server Database
The Windows Azure Marketplace
Lab: Using Cloud Data in a Data Warehouse Solution
Creating a SQL Azure Database
Extracting Data from a SQL Azure Database
Obtaining Data from the Windows Azure Marketplace
Module 9: 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: Deduplicating Data
Creating a Matching Policy
Using a DQS Project to Match Data
Module 10: Using Master Data Services
Introduction to Master Data Services
Implementing a Master Data Services Model
Using the Master Data Services Add-in for Excel
Lab: Implementing Master Data Services
Creating a Basic Model
Editing a Model by Using the Master Data Services Add-in for Excel
Loading Data into a Model
Enforcing Business Rules
Consuming Master Data Services Data
Module 11: Extending SQL Server Integration Services
Using Custom Components in SSIS
Using Scripts in SSIS
Lab: Using Custom Components and Scripts
Using a Custom Component
Using a Script Task
Module 12: Deploying and Configuring SSIS Packages
Overview of SSIS Deployment
Deploying SSIS Projects
Planning SSIS Package Execution
Lab: Deploying and Configuring SSIS Packages
Create a SSIS Catalog
Deploy an SSIS Project
Create Environments for an SSIS Solution
Running an SSIS Package in SQL Server Management Studio
Scheduling SSIS Packages with SQL Server Agent
Module 13: Consuming Data in a Data Warehouse
Introduction to Business Intelligence
Introduction to Reporting
Introduction to Data Analysis
Lab: Using Business Intelligence Tools
Exploring a Reporting Services Report
Exploring a PowerPivot Workbook
Exploring a Power View Report
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