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Implementing a Data Warehouse with Microsoft SQL Server (20463)
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EXCLUSIVE BENEFIT:
This course includes a twelve-month subscription to these exclusive benefits:
- 12 months of anytime access to your course labs and lab environment
- 12 months of 24/7 access to mentoring via chat, email, and phone
- 12 months of on-demand access to indexed, searchable recordings of your Online Live class
- 12 months of unlimited retakes of your class
COURSE INFORMATION
Implementing a Data Warehouse with Microsoft SQL Server (20463) Overview:
Implementing a Data Warehouse with Microsoft SQL Server (20463) course describes how to implement a data warehouse platform to support a BI solution.
You will learn how to:
- Create a data warehouse with Microsoft SQL Server 2014
- Implement ETL with SQL Server Integration Services
- Validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services
Note: This course is designed for customers who are interested in learning SQL Server 2012 or SQL Server 2014. It covers the new features in SQL Server 2014, but also the important capabilities across the SQL Server data platform.
Who Should Attend:
This course is intended for database professionals who need to create and support a data warehousing solution. Primary responsibilities include:
- Data warehouse implementation
- Developing SSIS packages for data extraction, transformation, and loading
- Enforcing data integrity by using Master Data Services
- Cleansing data by using Data Quality Services
Implementing a Data Warehouse with Microsoft SQL Server (20463) Prerequisites:
Before attending this course, you must have:
- At least 2 years experience of working with relational databases, including:
- Designing a normalized database.
- Creating tables and relationships.
- Querying with Transact-SQL.
- Some exposure to basic programming constructs (such as looping and branching).
- An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.
Implementing a Data Warehouse with Microsoft SQL Server (20463) Objectives:
After successfully completing this course, you will be able to:
- Describe data warehouse concepts and architecture considerations.
- Select an appropriate hardware platform for a data warehouse.
- Design a data warehouse implementation.
- Implement Data Flow in an SSIS Package.
- Implement Control Flow in an SSIS Package.
- Debug and Troubleshoot SSIS packages.
- Implement an ETL solution that supports incremental data extraction.
- Implement an ETL solution that supports incremental data loading.
- 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 BI solutions can consume data from the data warehouse.
Implementing a Data Warehouse with Microsoft SQL Server (20463) Outline:
Module 1: Introduction to Data Warehousing
- Overview of Data Warehousing
- Considerations for a Data Warehouse Solution
- Module 1 Labs: Explore a Data Warehouse Solution
Module 2: Planning Data Warehouse Infrastructure
- Considerations for Data Warehouse Infrastructure
- Planning Data Warehouse Hardware
- Module 2 Labs: Data Warehouse Infrastructure Planning
Module 3: Designing and Implementing a Data Warehouse
- Data Warehouse Design Overview
- Designing Dimension Tables
- Designing Fact Tables
- Physical Design for a Data Warehouse
- Module 3 Labs: Data Warehouse Implementation
Module 4: Creating an ETL Solution with SSIS
- Introduction to ETL with SSIS
- Exploring Data Sources
- Implementing Data Flow
- Module 4 Labs: Implement Data Flow in a SSIS Package
Module 5: Implementing Control Flow in an SSIS Package
- Introduction to Control Flow
- Creating Dynamic Packages
- Using Containers
- Managing Consistency
- Module 5 Labs:
- Implement Control Flow in a SSIS Package
- Transactions and Checkpoints Usage
Module 6: Debugging and Troubleshooting SSIS Packages
- Debugging an SSIS Package
- Logging SSIS Package Events
- Handling Errors in an SSIS Package
- Module 6 Labs: Debug and Troubleshoot a SSIS Package
Module 7: Implementing a Data Extraction Solution
- Planning Data Extraction
- Extracting Modified Data
- Module 7 Labs: Extract Modified Data
Module 8: Loading Data into a Data Warehouse
- Planning Data Loads
- Using SSIS for Incremental Loads
- Using Transact-SQL Loading Techniques
- Module 8 Labs: Data Warehouse Loading
Module 9: Enforcing Data Quality
- Introduction to Data Quality
- Using Data Quality Services to Cleanse Data
- Using Data Quality Services to Cleanse Data
- Module 9 Labs: Cleanse Data
Module 10: Master Data Services
- Introduction to Master Data Services
- Implementing a Master Data Services Model
- Managing Master Data
- Creating a Master Data Hub
- Module 10 Labs: Implement Master Data Services
Module 11: Extending SQL Server Integration Services
- Using Scripts in SSIS
- Using Custom Components in SSIS
- Module 11 Labs: Custom Scripts
Module 12: Deploying and Configuring SSIS Packages
- Overview of SSIS Deployment
- Deploying SSIS Projects
- Planning SSIS Package Execution
- Module 12 Labs: Deploy and Configure SSIS Packages
Module 13: Consuming Data in a Data Warehouse
- Introduction to Business Intelligence
- Enterprise Business Intelligence
- Self-Service BI and Big Data
- Module 13 Labs: Data Warehouse Usage in Enterprise and Self-Service BI Scenarios
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