OD20767

MOC on Demand: Implementing a SQL Data Warehouse

  • Course Price:$675
  • Audience: IT Professionals
  • Portfolio: MOC-ON-DEMAND
  • Related Exams:
  • Related Certifications:

Description

About MOC on Demand
MOC On Demand from OakTree puts a massive catalog of Microsoft courses online right at your fingertips -- from anywhere, anytime. Each MOC On Demand course is the perfect blend of video, text, and lab-style instruction with knowledge checks throughout so students can gauge their comprehension.  Taking official Microsoft courses online has never been so simple.

Basic Course Package: $675.00 or 2 voucher days
Package Includes: Online Course, 90-day access to the course and labs.
*does not include digital courseware.

Plus Course Package: $950.00 or 3 voucher days
Package Includes: Online Course, 90-day access to the course and labs, digital courseware

Premium Course Package: $1250.00 or 4 voucher days
Package Includes: Online Course, 180-day access to the course and labs, digital courseware.

Registration
Once you register for this course, you will receive a reply to your request within 1 business day from our friendly training staff to verify the Microsoft Online Courses Package of your choice.  Once a member of our staff has verified your payment details, you will receive your login credentials to begin taking the online Microsoft course.
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About this course
This course provides students with the knowledge and skills to provision a Microsoft SQL Server 2016 database. The course covers SQL Server 2016 provision both on-premise and in Azure, and covers installing from new and migrating from an existing install.

Audience profile
The primary audience for this course are 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. 

At course completion
After completing this course, students will be able to:

  • Provision a Database Server.
  • Upgrade SQL Server.
  • Configure SQL Server.
  • Manage Databases and Files (shared).

Prerequisites
In addition to their professional experience, students who attend this training should already have the following technical knowledge:
  • Basic knowledge of the Microsoft Windows operating system and its core functionality.
  • Working knowledge of relational databases.
  • Some experience with database design.

Course Outline

Module 1: Introduction to Data Warehousing

This module describes data warehouse concepts and architecture consideration.
Lessons
  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution
After completing this module, you will be able to:
  • Describe the key elements of a data warehousing solution
  • Describe the key considerations for a data warehousing solution

Module 2: Planning Data Warehouse Infrastructure
This module describes the main hardware considerations for building a data warehouse.
Lessons
  • Considerations for data warehouse infrastructure.
  • Planning data warehouse hardware.

After completing this module, you will be able to:
  • Describe the main hardware considerations for building a data warehouse
  • Explain how to use reference architectures and data warehouse appliances to create a data warehouse

Module 3: Designing and Implementing a Data Warehouse
This module describes how you go about designing and implementing a schema for a data warehouse.
Lessons
  • Designing dimension tables
  • Designing fact tables
  • Physical Design for a Data Warehouse
After completing this module, you will be able to:
  • Implement a logical design for a data warehouse
  • Implement a physical design for a data warehouse

Module 4: Columnstore Indexes
This module introduces Columnstore Indexes.
Lessons
  • Introduction to Columnstore Indexes
  • Creating Columnstore Indexes
  • Working with Columnstore Indexes
After completing this module, you will be able to:
  • Create Columnstore indexes
  • Work with Columnstore Indexes

Module 5: Implementing an Azure SQL Data Warehouse
This module describes Azure SQL Data Warehouses and how to implement them.
Lessons
  • Advantages of Azure SQL Data Warehouse
  • Implementing an Azure SQL Data Warehouse
  • Developing an Azure SQL Data Warehouse
  • Migrating to an Azure SQ Data Warehouse
  • Copying data with the Azure data factory
After completing this module, you will be able to:
  • Describe the advantages of Azure SQL Data Warehouse
  • Implement an Azure SQL Data Warehouse
  • Describe the considerations for developing an Azure SQL Data Warehouse
  • Plan for migrating to Azure SQL Data Warehouse

Module 6: Creating an ETL Solution
At the end of this module you will be able to implement data flow in a SSIS package.
Lessons
  • Introduction to ETL with SSIS
  • Exploring Source Data
  • Implementing Data Flow
After completing this module, you will be able to:
  • Describe ETL with SSIS
  • Explore Source Data
  • Implement a Data Flow

Module 7: Implementing Control Flow in an SSIS Package
This module describes implementing control flow in an SSIS package.
Lessons
  • Introduction to Control Flow
  • Creating Dynamic Packages
  • Using Containers
  • Managing consistency.
After completing this module, you will be able to:
  • Describe control flow
  • Create dynamic packages
  • Use containers

Module 8: Debugging and Troubleshooting SSIS Packages
This module describes how to debug and troubleshoot SSIS packages.
Lessons
  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in an SSIS Package
After completing this module, you will be able to:
  • Debug an SSIS package
  • Log SSIS package events
  • Handle errors in an SSIS package

Module 9: Implementing a Data Extraction Solution
This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.
Lessons
  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Loading modified data
  • Temporal Tables
After completing this module, you will be able to:
  • Describe incremental ETL
  • Extract modified data
  • Load modified data.
  • Describe temporal tables

Module 10: Enforcing Data Quality
This module describes how to implement data cleansing by using Microsoft Data Quality services.
Lessons
  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match Data
After completing this module, you will be able to:
  • Describe data quality services
  • Cleanse data using data quality services
  • Match data using data quality services
  • De-duplicate data using data quality services

Module 11: Using Master Data Services
This module describes how to implement master data services to enforce data integrity at source.
Lessons
  • Introduction to Master Data Services
  • Implementing a Master Data Services Model
  • Hierarchies and collections
  • Creating a Master Data Hub
After completing this module, you will be able to:
  • Describe the key concepts of master data services
  • Implement a master data service model
  • Manage master data
  • Create a master data hub

Module 12: Extending SQL Server Integration Services (SSIS)
This module describes how to extend SSIS with custom scripts and components.
Lessons
  • Using scripting in SSIS
  • Using custom components in SSIS
After completing this module, you will be able to:
  • Use custom components in SSIS
  • Use scripting in SSIS

Module 13: Deploying and Configuring SSIS Packages
This module describes how to deploy and configure SSIS packages.
Lessons
  • Overview of SSIS Deployment
  • Deploying SSIS Projects
  • Planning SSIS Package Execution
After completing this module, you will be able to:
  • Describe an SSIS deployment
  • Deploy an SSIS package
  • Plan SSIS package execution

Module 14: Consuming Data in a Data Warehouse
This module describes how to debug and troubleshoot SSIS packages.
Lessons
  • Introduction to Business Intelligence
  • An Introduction to Data Analysis
  • Introduction to reporting
  • Analyzing Data with Azure SQL Data Warehouse
After completing this module, you will be able to:
  • Describe at a high level business intelligence
  • Show an understanding of reporting
  • Show an understanding of data analysis
  • Analyze data with Azure SQL data warehouse