Implementing a Data Warehouse with Microsoft SQL Server 2014

Master the art of Implementing Data Warehouses with Microsoft SQL Server 2014 for database professionals seeking to excel in Business Intelligence solutions, including ETL processes, data cleansing, and data integrity management.

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Essential Skills Gained

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Design and implement a comprehensive data warehouse.

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Develop and manage robust ETL processes using SSIS.

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Ensure data integrity with Master Data Services.

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Enhance data quality with Data Quality Services.

Format

  • Instructor-led
  • 5 days with lectures and hands-on labs.

Audience

  • Database Professionals
  • Business Intelligence Developers
  • Data Warehouse Engineers
  • ETL Developers

Description

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.

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Upcoming Course Dates

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Course Outline

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Module 1: Introduction to Data Warehousing

  1. Overview of Data Warehousing

  2. Considerations for a Data Warehouse Solution

Lab: Exploring a Data Warehousing Solution

  1. Exploring Data Sources

  2. Exploring and ETL Process

  3. Exploring a Data Warehouse

Module 2: Planning Data Warehouse Infrastructure

  1. Considerations for Data Warehouse Infrastructure

  2. Planning Data Warehouse Hardware

Lab: Planning Data Warehouse Infrastructure

  1. Planning Data Warehouse Hardware

Module 3: Designing and Implementing a Data Warehouse

  1. Data Warehouse Design Overview

  2. Designing Dimension Tables

  3. Designing Fact Tables

  4. Physical Design for a Data Warehouse

Lab: Implementing a Data Warehouse

  1. Implement a Star Schema

  2. Implement a Snowflake Schema

  3. Implement a Time Dimension

Module 4: Creating an ETL Solution with SSIS

  1. Introduction to ETL with SSIS

  2. Exploring Data Sources

  3. Implementing Data Flow

Lab: Implementing Data Flow in an SSIS Package

  1. Exploring Data Sources

  2. Transferring Data by Using a Data Flow Task

  3. Using Transformations in a Data Flow

Module 5: Implementing Control Flow in an SSIS Package

  1. Introduction to Control Flow

  2. Creating Dynamic Packages

  3. Using Containers

  4. Managing Consistency

Lab: Implementing Control Flow in an SSIS Package

  1. Using Tasks and Precedence in a Control Flow

  2. Using Variables and Parameters

  3. Using Containers

Lab: Using Transactions and Checkpoints

  1. Using Transactions

  2. Using Checkpoints

Module 6: Debugging and Troubleshooting SSIS Packages

  1. Debugging an SSIS Package

  2. Logging SSIS Package Events

  3. Handling Errors in an SSIS Package

Lab: Debugging and Troubleshooting an SSIS Package

  1. Debugging an SSIS Package

  2. Logging SSIS Package Execution

  3. Implementing an Event Handler

  4. Handling Errors in a Data Flow

Module 7: Implementing a Data Extraction Solution

  1. Planning Data Extraction

  2. Extracting Modified Data

Lab: Extracting Modified Data

  1. Using a Datetime Column

  2. Using Change Data Capture

  3. Using the CDC Control Task

  4. Using Change Tracking

Module 8: Loading Data into a Data Warehouse

  1. Planning Data Loads

  2. Using SSIS for Incremental Loads

  3. Using Transact-SQL Loading Techniques

Lab: Loading a Data Warehouse

  1. Loading Data from CDC Output Tables

  2. Using a Lookup Transformation to Insert or Update Dimension Data

  3. Implementing a Slowly Changing Dimension

  4. Using the MERGE Statement

Module 9: Enforcing Data Quality

  1. Introduction to Data Quality

  2. Using Data Quality Services to Cleanse Data

Lab: Cleansing Data

  1. Creating a DQS Knowledge Base

  2. Using a DQS Project to Cleanse Data

  3. Using DQS in an SSIS Package

Module 10: Master Data Services

  1. Introduction to Master Data Services

  2. Implementing a Master Data Services Model

  3. Managing Master Data

  4. Creating a Master Data Hub

Lab: Implementing Master Data Services

  1. Creating a Master Data Services Model

  2. Using the Master Data Services Add-in for Excel

  3. Enforcing Business Rules

  4. Loading Data Into a Model

  5. Consuming Master Data Services Data

Module 11: Extending SQL Server Integration Services

  1. Using Scripts in SSIS

  2. Using Custom Components in SSIS

Lab: Using Custom Scripts

  1. Using a Script Task

Module 12: Deploying and Configuring SSIS Packages

  1. Overview of SSIS Deployment

  2. Deploying SSIS Projects

  3. Planning SSIS Package Execution

Lab: Deploying and Configuring SSIS Packages

  1. Creating an SSIS Catalog

  2. Deploying an SSIS Project

  3. Running an SSIS Package in SQL Server Management Studio

  4. Scheduling SSIS Packages with SQL Server Agent

Module 13: Consuming Data in a Data Warehouse

  1. Introduction to Business Intelligence

  2. Enterprise Business Intelligence

  3. Self-Service BI and Big Data

Lab: Using a Data Warehouse

  1. Exploring an Enterprise BI Solution

  2. Exploring a Self-Service BI Solution

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