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Implementing a Data Warehouse using Microsoft SQL Server

  • CMDBID 1173
  • Course Code QASQLETL
  • Duration 3 Days
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Microsoft Big Data Course

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Overview

This three-day instructor-led course provides students who wish to administer and maintain a SQL Server data warehouse and ETL infrastructure using SQL Server Integration Services (SSIS).

Target Audience

The primary audience for this course is individuals who will administer and maintain a SQL Server data warehouse and create and maintain SSIS packages.

Audience

After completing this course, students will be able to:
  • Design a data warehouse
  • Build a data warehouse
  • Implement ETL control and data tasks
  • Control transactions and maintain consistency
  • Implement incremental updates
  • Manage and run packages
  • Debug packages

Prerequisites

In addition to their professional experience, students who attend this training should already have the following technical knowledge:
Essential:
  • Basic knowledge of the Microsoft Windows operating system and its core functionality.
  • Working knowledge of Transact-SQL. (equivalent knowledge to QATSQL and QATSQLPLUS)
Nice to have:
  • Working knowledge of relational databases.
  • Some experience with database design.

Outline

Module 1 : Data warehouse Overview
This module introduces the main terms used within data warehousing.
Lessons:
  • What is a data warehouse?
  • Components of a data warehouse
  • Data warehouse project roles
  • Using SQL Server as a data warehousing solution
  • Lab diagram
Module 2: Designing and implementing a data warehouse
This module is aimed at designing and implementing the data warehouse. The first few lessons cover the design including fact tables and different variations of dimension table.
Lessons:
  • Dimensional Model
  • Dimensions and fact tables
  • Star and snowflake schemas
  • Slowly changing dimensions
  • Partitioned tables
  • Measures
  • Time and junk dimensions
  • Indexes and compression
  • LAB A: Designing a data warehouse
  • LAB B: Creating the data warehouse
  • LAB C: Create a fact table
  • LAB D: Create dimension tables
Module 3: Implementing a control flow in an SSIS package
This module looks at the tasks within the control flow of the SSIS package. The lessons will cover the tasks primarily aimed at the data warehouse.
Lessons:
  • Introduction to SSIS
  • Control flow
  • Advanced control flow
  • Containers
  • Precedence
  • Consistency
  • LAB A: Create a basic control flow task
  • LAB B: Using variable and parameters
  • LAB C: Using a for each loop
  • LAB D: Using transactions and checkpoints
 
Module 4: Implementing extract, transform and load with SSIS
This module covers the aspects of the SSIS package working with the data flow.
Lessons:
  • Introduction to extract, transform and load (ETL)
  • Data sources
  • Destinations and transformations
  • LAB A: Using the SQL Server import and export wizard
  • LAB B: Profiling a source
  • LAB C: Implement a data flow with transformations
Module 5: Debugging and troubleshooting SSIS packages.
This module covers the tools available to record events and handle errors.
Lessons:
  • SSIS debugging
  • SSIS event logging
  • Error handling
  • LAB A: Debugging an SSIS package
  • LAB B: Configuring event logging
  • LAB C: Implement error handling
Module 6: Implementing an incremental ETL process
This module covers the creation and running of a SSIS package for implementing the change data capture (CDC) tool.
Lessons:
  • Introduction to incremental extract, transform and load
  • Configuring incremental ETL
  • Keeping historical data
  • LAB A: Using CDC
  • LAB B: Implementing slowly changing dimensions
Module 7: Deploying and configuring SSIS packages
This module covers the deployment and scheduling of SSIS packages. The packages can use environment variables.
Lessons:
  • Package deployment options
  • Running SSIS packages
  • Validation and logging
  • LAB A: Creating an SSIS catalog, environments and deploying a project
  • LAB B: Running an SSIS package

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