MCSA BI

Overview

This 5 day 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.

Admission Requirements

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.

Available Exams and Certifications

This course will help you you prepare for the Exam 70-767. CLICK HERE to learn more about this exam.

This course contributes towards earning your MCSA: SQL 2016 BI Development. CLICK HERE to learn more.

Course Outcomes

After completing this course, students will be able to:

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

Module 1: Introduction to Data Warehousing 0/2
- Lecture 2.1
  
  Overview of Data Warehousing
- Lecture 2.2
  
  Considerations for a Data Warehouse Solution
Module 2: Planning Data Warehouse Infrastructure 0/2
- Lecture 3.1
  
  Considerations for data warehouse infrastructure.
- Lecture 3.2
  
  Planning data warehouse hardware.
Module 3: Designing and Implementing a Data Warehouse 0/3
- Lecture 4.1
  
  Designing dimension tables
- Lecture 4.2
  
  Designing fact tables
- Lecture 4.3
  
  Physical Design for a Data Warehouse
Module 4: Columnstore Indexes 0/3
- Lecture 5.1
  
  Introduction to Columnstore Indexes
- Lecture 5.2
  
  Creating Columnstore Indexes
- Lecture 5.3
  
  Working with Columnstore Indexes
Module 5: Implementing an Azure SQL Data Warehouse 0/5
- Lecture 6.1
  
  Advantages of Azure SQL Data Warehouse
- Lecture 6.2
  
  Implementing an Azure SQL Data Warehouse
- Lecture 6.3
  
  Developing an Azure SQL Data Warehouse
- Lecture 6.4
  
  Migrating to an Azure SQ Data Warehouse
- Lecture 6.5
  
  Copying data with the Azure data factory
Module 6: Creating an ETL Solution 0/3
- Lecture 7.1
  
  Introduction to ETL with SSIS
- Lecture 7.2
  
  Exploring Source Data
- Lecture 7.3
  
  Implementing Data Flow
Module 7: Implementing Control Flow in an SSIS Package 0/4
- Lecture 8.1
  
  Introduction to Control Flow
- Lecture 8.2
  
  Creating Dynamic Packages
- Lecture 8.3
  
  Using Containers
- Lecture 8.4
  
  Managing consistency
Module 8: Debugging and Troubleshooting SSIS Packages 0/3
- Lecture 9.1
  
  Debugging an SSIS Package
- Lecture 9.2
  
  Logging SSIS Package Events
- Lecture 9.3
  
  Handling Errors in an SSIS Package
Module 9: Implementing a Data Extraction Solution 0/4
- Lecture 10.1
  
  Introduction to Incremental ETL
- Lecture 10.2
  
  Extracting Modified Data
- Lecture 10.3
  
  Loading modified data
- Lecture 10.4
  
  Temporal Tables
Module 10: Enforcing Data Quality 0/3
- Lecture 11.1
  
  Introduction to Data Quality
- Lecture 11.2
  
  Using Data Quality Services to Cleanse Data
- Lecture 11.3
  
  Using Data Quality Services to Match Data
Module 11: Using Master Data Services 0/4
- Lecture 12.1
  
  Introduction to Master Data Services
- Lecture 12.2
  
  Implementing a Master Data Services Model
- Lecture 12.3
  
  Hierarchies and collections
- Lecture 12.4
  
  Creating a Master Data Hub
Module 12: Extending SQL Server Integration Services (SSIS) 0/2
- Lecture 13.1
  
  Using scripting in SSIS
- Lecture 13.2
  
  Using custom components in SSIS
Module 13: Deploying and Configuring SSIS Packages 0/2
- Lecture 14.1
  
  Overview of SSIS Deployment
- Lecture 14.2
  
  Deploying SSIS Projects
Module 14: Consuming Data in a Data Warehouse 0/4
- Lecture 15.1
  
  Introduction to Business Intelligence
- Lecture 15.2
  
  An Introduction to Data Analysis
- Lecture 15.3
  
  Introduction to reporting
- Lecture 15.4
  
  Analyzing Data with Azure SQL Data Warehouse