Course 20463-D: Implementing a Data Warehouse with Microsoft® SQL Server® 2014

Microsoft

Course 20463-D: Implementing a Data Warehouse with Microsoft® SQL Server® 2014

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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.

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.

Audience Profile

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: 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.

Prerequisites

Course outline

Module 1: Introduction to Data Warehousing

Module Overview

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

Overview of Data Warehousing
Considerations for a Data Warehouse Solution

Lab Sessions

Exploring a Data Warehousing Solution

Lab Lessons

Exploring Data Sources
Exploring an ETL Process
Exploring a Data Warehouse

After completing this module, students will be able to:

Describe the key elements of a data warehousing solution.
Describe the key considerations for a data warehousing project.

Module 2: Data Warehouse Hardware Considerations

Module Overview

This module discusses considerations for selecting hardware and distributing SQL Server facilities across servers.

Lessons

Considerations for building a Data Warehouse
Data Warehouse Reference Architectures and Appliances

Lab Sessions

Planning Data Warehouse Infrastructure

Lab Lessons

Planning Data Warehouse Hardware

After completing this module, students will be able to:

Describe key considerations for BI infrastructure.
Plan data warehouse infrastructure.

Module 3: Designing and Implementing a Data Warehouse

Module Overview

This module describes the key considerations for the logical design of a data warehouse, and then discusses best practices for its physical implementation.

Lessons

Logical Design for a Data Warehouse
Physical design for a data warehouse

Lab Sessions

Implementing a Data Warehouse Schema

Lab Lessons

Implement a Star Schema
Implementing a Snowflake Schema
Implementing a Time Dimension Table

After completing this module, students will be able to:

Describe a process for designing a dimensional model for a data warehouse.
Design dimension tables for a data warehouse.
Design fact tables for a data warehouse.
Design and implement effective physical data structures for a data warehouse.

Module 4: Creating an ETL Solution with SSIS

Module Overview

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

Introduction to ETL with SSIS
Exploring Data Sources
Implementing Data Flow

Lab Sessions

Implementing Data Flow in an SSIS Package

Lab Lessons

Exploring Source Data
Transferring Data by Using a Data Flow Task
Using Transformations in a Data Flow

After completing this module, students will be able to:

Describe the key features of SSIS.
Explore source data for an ETL solution.
Implement a data flow by using SSIS.

Module 5: Implementing Control Flow in an SSIS Package

Module Overview

This module describes how to implement ETL solutions that combine multiple tasks and workflow logic.

Lessons

Introduction to Control Flow
Creating Dynamic Packages
Using Containers
Managing Consistency

Lab Sessions

Implementing Control Flow in an SSIS Package
Using Transactions and Checkpoints

Lab Lessons

Using Tasks and Precedence in a Control Flow
Using Variables and Parameters
Using Containers
Using Transactions
Using Checkpoints

After completing this module, students will be able to:

Implement control flow with tasks and precedence constraints.
Create dynamic packages that include variables and parameters.
Use containers in a package control flow.
Enforce consistency with transactions and checkpoints.

Module 6: Debugging and Troubleshooting SSIS Packages

Module Overview

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

Debugging an SSIS Package
Logging SSIS Package Events
Handling Errors in an SSIS Package

Lab Sessions

Debugging and Troubleshooting an SSIS Package

Lab Lessons

Debugging an SSIS Package
Logging SSIS Package Execution
Implementing an Event Handler
Handling Errors in a Data Flow

After completing this module, students will be able to:

Debug an SSIS package.
Implement logging for an SSIS package.
Handle errors in an SSIS package.

Module 7: Implementing a Data Extraction Solution

Module Overview

This module describes the techniques you can use to implement an incremental data warehouse refresh process.

Lessons

Planning Data Extraction
Extracting Modified Data

Lab Sessions

Extracting Modified Data

Lab Lessons

Using a Datetime Column to Incrementally Extract Data
Using Change Data Capture
Using the CDC Control Task
Using Change Tracking

After completing this module, students will be able to:

Plan data extraction.
Extract modified data.

Module 8: Loading Data into a Data Warehouse

Module Overview

This module describes the techniques you can use to implement a data warehouse load process.

Lessons

Planning Data Loads
Using SSIS for Incremental Loads
Using Transact-SQL Loading Techniques

Lab Sessions

Loading a Data Warehouse

Lab Lessons

Loading Data from CDC Output Tables
Using a Lookup Transformation to Insert or Update Dimension Data
Implementing a Slowly Changing Dimension
Using the MERGE Statement

After completing this module, students will be able to:

Describe the considerations for planning data loads.
Use SQL Server Integration Services (SSIS) to load new and modified data into a data warehouse.
Use Transact-SQL techniques to load data into a data warehouse.

Module 9: Enforcing Data Quality

Module Overview

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

Introduction to Data Quality
Using Data Quality Services to Cleanse Data
Using Data Quality Services to Match Data

Lab Sessions

Cleansing Data
Deduplicating Data

Lab Lessons

Creating a DQS Knowledge Base
Using a DQS Project to Cleanse Data
Using DQS in an SSIS Package
Creating a Matching Policy
Using a DQS Project to Match Data

After completing this module, students will be able to:

Describe how DQS can help you manage data quality.
Use DQS to cleanse your data.
Use DQS to match data.

Module 10: Master Data Services

Module Overview

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

Introduction to Master Data Services
Implementing a Master Data Services Model
Managing Master Data
Creating a Master Data Hub

Lab Sessions

Implementing Master Data Services

Lab Lessons

Creating a Master Data Services Model
Using the Master Data Services Add-in for Excel
Enforcing Business Rules
Loading Data into a Model
Consuming Master Data Services Data

After completing this module, students will be able to:

Describe the key concepts of Master Data Services.
Implement a Master Data Services model.
Use Master Data Services tools to manage master data.
Use Master Data Services tools to create a master data hub.

Module 11: Extending SQL Server Integration Services

Module Overview

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

Using Scripts in SSIS
Using Custom Components in SSIS

Lab Sessions

Using Custom Scripts

Lab Lessons

Using a Script Task

After completing this module, students will be able to:

Include custom scripts in an SSIS package.
Describe how custom components can be used to extend SSIS.

Module 12: Deploying and Configuring SSIS Packages

Module Overview

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

Overview of SSIS Deployment
Deploying SSIS Projects
Planning SSIS Package Execution

Lab Sessions

Deploying and Configuring SSIS Packages

Lab Lessons

Creating an SSIS Catalog
Deploying an SSIS Project
Creating Environments for an SSIS Solution
Running an SSIS Package in SQL Server Management Studio
Scheduling SSIS Packages with SQL Server Agent

After completing this module, students will be able to:

Describe considerations for SSIS deployment.
Deploy SSIS projects.
Plan SSIS package execution.

Module 13: Consuming Data in a Data Warehouse

Module Overview

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

Introduction to Business Intelligence
Enterprise Business Intelligence
Self-Service BI and Big Data

Lab Sessions

Using a Data Warehouse

Lab Lessons

Exploring an Enterprise BI Solution
Exploring a Self-Service BI Solution

After completing this module, students will be able to:

Describe BI and common BI scenarios.
Describe how a data warehouse can be used in enterprise BI scenarios.
Describe how a data warehouse can be used in self-service BI scenarios.

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