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Aron Mesterbasic
On this immersed 5 day MCSA: SQL Server 2016 Business Intelligence Development course, you'll learn to implement a SQL Server 2016 data warehouse solution to support a business intelligence.
Your course package is designed to provide maximum learning and convenience. This is included in the price of your course:
Your expert instructor will get you ready for the following exams and certifications, which are included in your course package and covered by the Certification guarantee.
It is recommended you have at least 2 years’ experience of working with relational databases, including:
Designing a normalised database
Creating tables and relationships
Some exposure to basic programming constructs (such as looping and branching)
An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable
Using our engaging learning methodology including a variety of tools, we’ll cover the entire curriculum.
Course 20767A: Implementing a SQL Data Warehouse
Module 1: Introduction to Data Warehousing
Describe data warehouse concepts and architecture considerations.
Lessons
- Overview of Data Warehousing
- Considerations for a Data Warehouse Solution
Lab : Exploring 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 Building a Data Warehouse
- Data Warehouse Reference Architectures and Appliances
Lab : Planning Data Warehouse Infrastructure
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
- Logical Design for a Data Warehouse
- Physical Design for a Data Warehouse
Lab : Implementing a Data Warehouse Schema
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
Lab : Using 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
Lab : Implementing an Azure SQL Data Warehouse
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
Lab : Implementing Data Flow in an SSIS Package
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
Lab : Implementing Control Flow in an SSIS Package
Lab : Using Transactions and Checkpoints
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
Lab : Debugging and Troubleshooting 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 an Incremental ETL Process
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
- Temporal Tables
Lab : Extracting Modified Data
Lab : Loading Incremental Changes
After completing this module, you will be able to:
- Describe incremental ETL
- Extract 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
Lab : Cleansing Data
Lab : De-duplicating 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
- Master Data Services Concepts
- Implementing a Master Data Services Model
- Managing Master Data
- Creating a Master Data Hub
Lab : Implementing Master Data Services
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 Custom Components in SSIS
- Using Scripting in SSIS
Lab : Using Scripts and Custom Components
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
Lab : Deploying and Configuring SSIS Packages
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
- Introduction to Reporting
- An Introduction to Data Analysis
- Analysing Data with Azure SQL Data Warehouse
Lab : Using Business Intelligence Tools
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
- Analyse data with Azure SQL data warehouse
Course 20768A: Developing SQL Data Models
Module 1: Introduction to Business Intelligence and Data Modeling
This module introduces key BI concepts and the Microsoft BI product suite
Lessons
- Introduction to Business Intelligence
- The Microsoft business intelligence platform
Lab: Exploring a Data Warehouse
After are completing this module, you will be editable to:
- Describe the concept of business intelligence
- Describe the Microsoft business intelligence platform
Module 2: Creating Multidimensional Databases
This module describes the steps required to create a multidimensional database with analysis services
Lessons
- Introduction to multidimensional analysis
- Creating data sources and data source views
- Creating a cube
- Overview of cube security
Lab: Creating a multidimensional database
After are completing this module, you will be editable to:
- Use multidimensional analysis
- Create data sources and data source views
- Create a cube
- Describe cube security
Module 3: Working with Cubes and Dimensions
This module describes how to implement dimensions into a cube
Lessons
- Configuring dimensions
- Define attribute hierarchies
- Sorting and grouping attributes
Lab: Working with Cubes and Dimensions
After are completing this module, you will be editable to:
- Configure dimensions
- Define attribute hierarchies.
- Sort and group attributes
Module 4: Working with Measures and Measure Groups
This module describes how to implement Measures and measure groups in a cube
Lessons
- Working with Measures
- Working with measure groups
Lab: Configuring Measures and Measure Groups
After are completing this module, you will be editable to:
- Work with Measures
- Work with measure groups
Module 5: Introduction to MDXT
This module describes the MDX syntax and how to use MDX
Lessons
- MDX fundamentals
- Adding calculations to a cube
- Using MDX to query a cube
Lab: Using MDX
After are completing this module, you will be editable to:
- Describe the fundamentals of MDX
- Add calculations to a cube
- Query a cube using MDX
Module 6: Customising Cube Functionality
This module describes how to customise a cube
Lessons
- Implementing key performance indicators
- Implementing actions
- Implementing perspectives
- Implementing translations
Lab: Customising a Cube
After are completing this module, you will be editable to:
- Implement key performance indicators
- Implement actions
- Implement perspectives
- Implement translations
Module 7: Implementing a Tabular Data Model by Using Analysis Services
This module describes how to implement a tabular data model in PowerPivot
Lessons
- Introduction to tabular data models
- Creating a tabular data model
- Using an Analysis Services tabular model in an enterprise BI solution
Lab: Working with an Analysis Services tabular data model
After are completing this module, you will be editable to:
- Describe tabular data models
- Create a tabular data model
- Be printable to use an Analysis Services tabular data model into an enterprise BI solution
Module 8: Introduction to Data Analysis Expression (DAX)
This module describes how to use DAX to create Measures and Calculated columns in a tabular data model
Lessons
- DAX fundamentals
- Using DAX to create Calculated Columns and Measures in a tabular data model
Lab: Creating Calculated Columns and Measures by using DAX
After are completing this module, you will be editable to:
- Describe the fundamentals of DAX
- Use DAX to create Calculated Columns and Measures in a tabular data model
Module 9: Performing Predictive Analysis with Data Mining
This module describes how to use data mining for predictive analysis
Lessons
- Overview of data mining
- Using the data mining add-in for Excel
- Creating a custom data mining solution
- Validating a data mining model
- Connecting to and consuming a data mining model
Lab: Perform Predictive Analysis with Data Mining
After are completing this module, you will be editable to:
- Describe data mining
- Use the data mining add-in for Excel
- Create a custom data mining solution
- Validate a data mining solution
- Connect to and consume a data mining solution
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