Implementing a Data Warehouse with Microsoft SQL Server Training

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  • Project Based Learning
  • Certified & Experienced Trainers
  • Course Completion Certificate
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Implementing a Data Warehouse with Microsoft SQL Server Training Course Overview

The training provides the proper knowledge to the candidate that allows them to validate data with SQL Server Data Quality Services and SQL Server Master Data Services. This course lays emphasis on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing. The training provides the skills required to Implement data cleansing by using Microsoft Data Quality Services and Implement Master Data Services to enforce data integrity.

Implementing a Data Warehouse with Microsoft SQL Server Course Objectives
  • Describe data warehouse concepts and architecture considerations.
  • Design and implement a data warehouse.
  • Select an appropriate hardware platform for a data warehouse.
  • Implement Data Flow and Control Flow in an SSIS Package.
  • Debug and Troubleshoot SSIS packages.
  • Implement an SSIS solution that supports incremental data warehouse loads and changing data.
Target audience
  • Business intelligence professionals
  • Database developers
  • SQL Server database administrators
  • System engineers
  • Database professionals who are involved in installation, configuration, and maintenance tasks
Prerequisites

To attend this training, the student should know how to write T-SQL Queries for Microsoft SQL Server .

Implementing a Data Warehouse with Microsoft SQL Server Course Certificate

To attend this training, the student should know how to write T-SQL Queries for Microsoft SQL Server .

Implementing a Data Warehouse with Microsoft SQL Server Training Course Content

Introduction

  • Store information in a data warehouse
  • What you should know
  • Set up the example databases

1. Data Warehouse Foundations

  • Data warehouse core concepts
  • Transactional databases vs. data warehouses
  • Dimensions and facts
  • Star and snowflake schemas
  • Hardware and infrastructure

2. Create a Data Warehouse

  • Create a data warehouse in SQL Server
  • Design dimension tables
  • Design fact tables
  • Create an indexed view

3. Columnstore Indexes

  • Advantages of columnstore indexes
  • Memory-optimized columnstore table
  • Rebuild columnstore indexes

4. Implement an Azure SQL Data Warehouse

  • Hosting a data warehouse in the cloud
  • Create an Azure SQL Data Warehouse project
  • Develop tables in Azure SQL Data Warehouse
  • The Data Warehouse Migration Utility
  • Migrate a data warehouse to Azure
  • Pause and remove an Azure data warehouse

5. Extract, Transform, and Load (ETL)

  • What is ETL and SQL Server Integration Services (SSIS)?
  • Understand data flow
  • Establish control flow

6. Enforce Data Quality

  • SQL Server Data Quality Services (DQS)
  • Cleanse data with DQS
  • Create a custom knowledge base

7. Master Data Services

  • Introduction to Master Data Services (MDS)
  • Install MDS and IIS
  • Configure Master Data Services
  • Deploy a sample MDS model
  • Install the MDS Excel add-in
  • Update master data in Excel

8. Consume Data from the Warehouse

  • Business intelligence applications

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