Instructor-led (classroom)
Advanced
5 days
English
This course describes how to implement a data warehouse platform to support a BI solution. Students will learn how to create a data warehouse with Microsoft® SQL Server® 2014, implement ETL with SQL Server Integration Services, and 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.
This course is intended for database professionals who need to fulfil a Business 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:
A 360-degree learning approach that you can adapt to your learning style
Engage and learn more with these live and highly-interactive classes alongside your peers
24/7 Teaching Assistance Keep engaged with integrated teaching
Projects provide you with sample work to show prospective employers.
Real-world projects relevant to what you’re learning throughout the program
A support team focused on helping you succeed alongside a peer community
After completing this course, students will be able to:
Introduction to Data Warehousing
This module provides an introduction to the key components of a data warehousing solution and the high-level considerations you must take into account when you embark on a data warehousing project.
Lessons
Lab: Exploring a Data Warehousing Solution
After completing this module, student will be able to:
Data Warehouse Hardware Considerations
This module discusses considerations for selecting hardware and distributing SQL Server facilities across servers.
Lessons
Lab: Planning Data Warehouse Infrastructure
After completing this module, students will be able to:
Designing and Implementing a Data Warehouse
This module describes the key considerations for the logical design of a data warehouse, and then discusses best practices for its physical implementation.
Lessons
Lab: Implementing a Data Warehouse Schema
After completing this module, students will be able to:
Creating an ETL Solution with SSIS
This module discusses considerations for implementing an ETL process, and then focuses on Microsoft SQL Server Integration Services (SSIS) as a platform for building ETL solutions.
Lessons
Lab: Implementing Data Flow in an SSIS Package
After completing this module, students will be able to:
Implementing Control Flow in an SSIS Package
This module describes how to implement ETL solutions that combine multiple tasks and workflow logic.
Lessons
Lab: Implementing Control Flow in an SSIS Package
Lab:Using Transactions and Checkpoints
After completing this module, students will be able to:
Debugging and Troubleshooting SSIS Packages
This module describes how you can debug packages to find the cause of errors that occur during execution. It then discusses the logging functionality built into SSIS that you can use to log events for troubleshooting purposes. Finally, the module describes common approaches for handling errors in control flow and data flow.
Lessons
Lab: Debugging and Troubleshooting an SSIS Package
After completing this module, students will be able to:
Implementing a Data Extraction Solution
This module describes the techniques you can use to implement an incremental data warehouse refresh process.
Lessons
Lab: Extracting Modified Data
After completing this module, students will be able to:
Loading Data into a Data Warehouse
This module describes the techniques you can use to implement a data warehouse load process.
Lessons
Lab: Loading a Data Warehouse
After completing this module, students will be able to:
Enforcing Data Quality
Ensuring the high quality of data is essential if the results of data analysis are to be trusted. SQL Server 2014 includes Data Quality Services (DQS) to provide a computer-assisted process for cleansing data values, as well as identifying and removing duplicate data entities. This process reduces the workload of the data steward to a minimum while maintaining human interaction to ensure accurate results
Lessons
Lab : Cleansing Data
Lab: Deduplicating Data
After completing this module, students will be able to:
Master Data Services
Master Data Services provides a way for organizations to standardize and improve the quality, consistency, and reliability of the data that guides key business decisions. This module introduces Master Data Services and explains the benefits of using it.
Lessons
Lab: Implementing Master Data Services
After completing this module, students will be able to:
Extending SQL Server Integration Services
This module describes the techniques you can use to extend SSIS. The module is not designed to be a comprehensive guide to developing custom SSIS solutions, but to provide an awareness of the fundamental steps required to use custom components and scripts in an ETL process, based on SSIS.
Lessons
Lab: Using Custom Scripts
After completing this module, students will be able to:
Deploying and Configuring SSIS Packages
Microsoft SQL Server Integration Services (SSIS) provides tools that make it easy to deploy packages to another computer. The deployment tools also manage any dependencies, such as configurations and files that the package needs. In this module, you will learn how to use these tools to install packages and their dependencies on a target computer.
Lessons
Lab: Deploying and Configuring SSIS Packages
After completing this module, students will be able to:
Consuming Data in a Data Warehouse
This module introduces BI, describing the components of Microsoft SQL Server that you can use to create a BI solution, and the client tools with which users can create reports and analyze data.
Lessons
Lab: Using a Data Warehouse
After completing this module, students will be able to:
Implementing a Data Warehouse with Microsoft SQL Server 2012/2014
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