Implementing A Data Warehouse with Microsoft SQL Server 2012
Course
In London
Description
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Type
Course
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Location
London
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Duration
5 Days
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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About this course
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.
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Subjects
- Data warehousing
- Server
- SQL
- SQLite
- Quality
- Warehousing
- Quality Training
- SQL Database
- SQL Server
- Sql training
- SQLOS
- SQL Server Scheduling
Course programme
- 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
- Copyrights © 2014, Acuity Training. All Rights reserved. – 3 –
- 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
Implementing A Data Warehouse with Microsoft SQL Server 2012