This 4 day course describes how to implement a BI platform to support information worker analytics. Students will learn how to create a data warehouse with Microsoft®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.

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After completing this course, students will be able to:

  • 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.

This course is intended for database professionals who need to fulfil a Business (BI) Intelligence Developer role. They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing. Primary responsibilities include:

  • Implementing a data warehouse.
  • Developing SSIS packages for data extraction, transformation, and loading.
  • Enforcing data integrity by using Master Data Services.
  • Cleansing data by using Data Quality Services.
  •   Lesson 1: Overview of Data Warehousing
  •   Lesson 2: Considerations for a Data Warehouse Solution
  •   Lab 1: Exploring a Data Warehousing Solution
  •   Lesson 1: Considerations for Building a Data Warehouse
  •   Lesson 2: Data Warehouse Reference Architectures and Appli
  •   Lesson 1: Logical Design for a Data Warehouse
  •   Lesson 2: Physical Design for a Data Warehouse
  •   Lab 3: Implementing a Data Warehouse Schema
  •   Lesson 1: Introduction to ETL with SSIS
  •   Lesson 2: Exploring Source Data
  •   Lesson 3: Implementing Data Flow
  •   Lab 4: Implementing Data Flow in an SSIS Package
  •   Lesson 1: Introduction to Control Flow
  •   Lesson 2: Creating Dynamic Packages
  •   Lesson 3: Using Containers
  •   Lab 5A: Implementing Control Flow in an SSIS Package
  •   Lesson 4: Managing Consistency
  •   Lab 5B: Using Transactions and Checkpoints
  •   Lesson 1: Debugging an SSIS Package
  •   Lesson 2: Logging SSIS Package Events
  •   Lesson 3: Handling Errors in an SSIS Package
  •   Lab 6: Debugging and Troubleshooting an SSIS Package
  •   Lesson 1: Introduction to Incremental ETL
  •   Lesson 2: Extracting Modified Data
  •   Lab 7A: Extracting Modified Data
  •   Lesson 3: Loading Modified Data
  •   Lab 7B: Loading Incremental Changes
  •   Lesson 1: Introduction to Data Quality
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  •   Lesson 2: Using Data Quality Services to Cleanse Data
  •   Lab 8A: Cleansing Data
  •   Lesson 3: Using Data Quality Services to Match Data
  •   Lab 8B: Deduplicating Data
  • Lesson 1: Introduction to Master Data Services
  •   Lesson 2: Implementing a Master Data Services Model
  •   Lesson 3: Managing Master Data
  •   Lesson 4: Creating a Master Data Hub
  •   Lab 9: Implementing Master Data Services
  •   Lesson 1: Using Custom Components in SSIS
  •   Lesson 2: Using Scripts in SSIS
  •   Lab 10: Using Custom Components and Scripts
  •   Lesson 1: Overview of SSIS Deployment
  •   Lesson 2: Deploying SSIS Projects
  •   Lesson 3: Planning SSIS Package Execution
  •   Lab 11: Deploying and Configuring SSIS Packages
  • Lesson 1: Introduction to Business Intelligence
  •   Lesson 2: Introduction to Reporting
  •   Lesson 3: Introduction to Data Analysis
  •   Lab 12: Using Business Intelligence Tools
Dates & Prices

This course is run by arrangement for private groups and 1-2-1 sessions.

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