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Course Description
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.
At Course Completion
- Provision a Database Server.
- Upgrade SQL Server.
- Configure SQL Server.
- Manage Databases and Files (shared).
Who is the target audience?
- 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.
Microsoft Official Courses
Microsoft Official Courses On-Demand (MOC On-Demand) are authorized Microsoft official courses exclusively developed by Microsoft Certified Trainers. MOC on-demand delivers a comprehensive training experience comprising a merge of high-quality audiovisuals, academic readings, Microsoft labs online and knowledge check/assessments.
MOC on-demand is a self-paced training structured for IT Professionals and Developers which makes them proficient in the Microsoft technology and develop technical skills. It focusses on providing you a live, real-time environment for hands-on training while including all the interactive features with credible content that other On-demand offerings lack.
MOC On-Demand comprises a range of courses which are structured in a modular format consisting different modules that are further segregated into lessons, each of which contains questions to testify your knowledge.
MOC On-Demand - Features that make it the best
Self-paced learning
An online course structure which gives you utmost flexibility to learn.
Official Microsoft content
HD-quality streaming videos with interactive content delivered by expert instructors -“straight from the source”.
Digital Microsoft Official Curriculum
Access to the official curriculum anywhere & anytime.
Hands-on live labs
Microsoft Labs Online to work on your technical skills with integrated lab steps.
Knowledge assessments
Knowledge check and instant feedback to mark your stand in the training process.
24x7 availability
Microsoft-hosted mentors available to you round the clock via chat, email, & phone.
Authored by Microsoft certified experts
In-depth technical content structured by individuals who wrote the software and delivered by expert instructors.
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
Lab : Exploring a Data Warehouse Solution
- Exploring data sources
- Exploring an ETL process
- Exploring a data warehouse
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.
Lab : Planning Data Warehouse Infrastructure
- Planning data warehouse hardware
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
Lab : Implementing a Data Warehouse Schema
- Implementing a star schema
- Implementing a snowflake schema
- Implementing a time dimension table
Module 4: Column store Indexes
This module introduces Columnstore Indexes.Lessons
- Introduction to Columnstore Indexes
- Creating Columnstore Indexes
- Working with Columnstore Indexes
Lab : Using Columnstore Indexes
- Create a Columnstore index on the FactProductInventory table
- Create a Columnstore index on the FactInternetSales table
- Create a memory optimized Columnstore table
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
Lab : Implementing an Azure SQL Data Warehouse
- Create an Azure SQL data warehouse database
- Migrate to an Azure SQL Data warehouse database
- Copy data with the Azure data factory
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
Lab : Implementing Data Flow in an SSIS Package
- Exploring source data
- Transferring data by using a data row task
- Using transformation components in a data row
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.
Lab : Implementing Control Flow in an SSIS Package
- Using tasks and precedence in a control flow
- Using variables and parameters
- Using containers
Lab : Using Transactions and Checkpoints
- Using transactions
- Using checkpoints
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
Lab : Debugging and Troubleshooting an SSIS Package
- Debugging an SSIS package
- Logging SSIS package execution
- Implementing an event handler
- Handling errors in data flow
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
Lab : Extracting Modified Data
- Using a datetime column to incrementally extract data
- Using change data capture
- Using the CDC control task
- Using change tracking
Lab : Loading a data warehouse
- Loading data from CDC output tables
- Using a lookup transformation to insert or update dimension data
- Implementing a slowly changing dimension
- Using the merge statement
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
Lab : Cleansing Data
- Creating a DQS knowledge base
- Using a DQS project to cleanse data
- Using DQS in an SSIS package
Lab : De-duplicating Data
- Creating a matching policy
- Using a DS project to match data
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
Lab : Implementing Master Data Services
- Creating a master data services model
- Using the master data services add-in for Excel
- Enforcing business rules
- Loading data into a model
- Consuming master data services data
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
Lab : Using scripts
- Using a script task
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
Lab : Deploying and Configuring SSIS Packages
- Creating an SSIS catalog
- Deploying an SSIS project
- Creating environments for an SSIS solution
- Running an SSIS package in SQL server management studio
- Scheduling SSIS packages with SQL server agent
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
Lab : Using a data warehouse
- Exploring a reporting services report
- Exploring a PowerPivot workbook
- Exploring a power view report
What you’ll get in your subscription
Full access to the official Digital Microsoft Official Courseware (dMOC)
Microsoft’s HD-quality streaming videos
Access to Hands-On, Live Lab
Microsoft Training Support 24*7
Exercises, Readings and Knowledge checks
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.
