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LinkedIn Learning

Implementing a Data Warehouse with Microsoft SQL Server 2012

via LinkedIn Learning

Overview

Syllabus

Introduction
  • Welcome
  • What you should know
  • Using the exercise files
1. Setting Up the Environment
  • Finding and downloading SQL Server 2012 trial edition
  • Installing SQL Server 2012 trial edition
  • Finding and installing the sample data
2. Introduction to Data Warehousing
  • Overview of data warehousing
  • Understanding the differences between typical databases and data warehouses
  • Implementing a data warehouse using a SQL database engine
3. Designing a Data Warehouse
  • Logical design for a data warehouse
  • Choosing between star and snowflake schema design techniques
  • Physical design for a data warehouse
4. Data Warehouse Hardware
  • Considerations for building a data warehouse
  • Data warehouse reference architectures
  • Appliances and big data
5. Creating an Extract Transform and Load (ETL) Solution with SQL Server Integration Services (SSIS)
  • Introduction to ETL with SSIS
  • Exploring source data
  • Introduction to control flow
  • Implementing data flow
6. Debugging and Troubleshooting SSIS Packages
  • Debugging an SSIS package
  • Logging SSIS package events
  • Handling errors in an SSIS package
7. Implementing an Incremental ETL Process
  • Introduction to incremental ETL
  • Extracting modified data
  • Loading modified data
  • Working with slowly changing dimensions
8. Deploying and Configuring SSIS Packages
  • Installing and maintaining SSIS components
  • Deploying SSIS solutions
  • Using SQL Server Agent to execute an ETL package
  • Configuring advanced SSIS settings
9. Enforcing Data Quality
  • Installing Data Quality Services
  • Using Data Quality Services to cleanse data
  • Using Data Quality Services to find duplicate data
  • Utilizing Data Quality Services in an SSIS data flow
10. Consuming Data in a Data Warehouse
  • Introduction to business intelligence
  • Using Reporting Services with a data warehouse
  • Introduction to data analysis with SQL Server Analysis Services (SSAS)
Conclusion
  • Next steps

Taught by

Martin Guidry

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