MCSA- SQL Server 2016 Business Intelligence Development Training

·      Lessons

·      Overview of Data Warehousing

·      Considerations for a Data Warehouse Solution

·      Lab

·      Exploring a Data Warehousing Solution               

·      Lessons

·      Considerations for Data Warehouse Infrastructure

·      Planning Data Warehouse Hardware

·      Lab

·      Planning Data Warehouse Infrastructure              

·      Lessons

·      Data Warehouse Design Overview

·      Designing Dimension Tables

·      Designing Fact Tables

·      Physical Design for a Data Warehouse

·      Lab

·      Implementing a Data Warehouse              

·      Lessons

·      Introduction to Column store Indexes

·      Creating Column store Indexes

·      Working with Column store Indexes

·      Lab

·      Using Column store Indexes                     

·      Lessons

·      Advantages of Azure SQL Data Warehouse

·      Implementing an Azure SQL Data Warehouse Database

·      Developing an Azure SQL Data Warehouse

·      Migrating to an Azure SQL Data Warehouse

·      Copying Data with the Azure Data Factory

·      Lab

·      Implement an Azure SQL Data Warehouse                     

·      Lessons

·      Introduction to ETL with SSIS

·      Exploring Source Data

·      Implementing Data Flow

·      Lab

·      Implementing Data 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 Transactions and Checkpoints                    

·      Lessons

·      Debugging an SSIS Package

·      Logging SSIS Package Events

·      Handling Errors in an SSIS Package

·      Lab

·      Debugging and Troubleshooting an SSIS Package                      

·      Lessons

·      Introduction to Incremental ETL

·      Extracting Modified Data

·      Loading Modified Data

·      Temporal Tables

·      Lab

·      Extracting Modified Data

·      Loading a Data Warehouse                       

·      Lecture 10: Enforcing Data Quality

·      Lessons

·      Introduction to Data Quality

·      Using Data Quality Services to Cleanse Data

·      Using Data Quality Services to Match Data

·      Lab

·      Cleansing Data

·      Duplicating Data               

·      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 Model                      

·      Lessons

·      Using Scripts in SSIS

·      Using Custom Components in SSIS

·      Lab

·      Using Custom Scripts                   

·      Lessons

·      Overview of SSIS Development 13-2

·      Deploying SSIS Projects 13-5

·      Planning SSIS Package Execution 13-14

·      Lab

·      Deploying and Configuring SSIS Packages                     

·      Lessons

·      Introduction to Business Intelligence

·      Introduction to Data Analysis

·      Introduction to Reporting

·      Analysing Data with Azure SQL Data Warehouse

·      Lab

·      Using a Data Warehouse               

Developing SQL Data Models course imparts core skills to implement multidimensional databases using SSAS (SQL Server Analysis Services), and create tabular semantic data models for analysis. This SSAS training is meant for database professionals who create enterprise BI solutions in order to fulfil the role of a BI Developer. This SQL Data Model Development course is also suitable for power users, information workers and data analysts.

This Lecture 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 completing this Lecture, you will be able to:

·      Describe the concept of business intelligence

·      Describe the Microsoft business intelligence platform                 

This Lecture describes the steps required to create a multidimensional database with analysis services.

·      Lessons

·      Introduction to multidimensional analysis

·      Course details

·      Creating data sources and data source views

·      Creating a cube

·      Overview of cube security

·      Lab : Creating a multidimensional database

·      After completing this Lecture, you will be able to:

·      Use multidimensional analysis

·      Create data sources and data source views

·      Create a cube

·      Describe cube security                  

This Lecture describes how to implement dimensions in a cube.

·      Lessons

·      Configuring dimensions

·      Define attribute hierarchies

·      Sorting and grouping attributes

·      Lab : Working with Cubes and Dimensions

·      After completing this Lecture, you will be able to:

·      Configure dimensions

·      Define attribute hierarchies.

·      Sort and group attributes              

This Lecture 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 completing this Lecture, you will be able to:

·      Work with measures

·      Work with measure groups           

This Lecture 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 completing this Lecture, you will be able to:

·      Describe the fundamentals of MDX

·      Add calculations to a cube

·      Query a cube using MDX             

This Lecture describes how to customize a cube.

·      Lessons

·      Implementing key performance indicators

·      Implementing actions

·      Implementing perspectives

·      Implementing translations

·      Lab : Customizing a Cube

·      After completing this Lecture, you will be able to:

·      Implement key performance indicators

·      Implement actions

·      Implement perspectives

·      Implement translations                  

This Lecture describes how to implement a tabular data model in Power Pivot.

·      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 completing this Lecture, you will be able to:

·      Describe tabular data models

·      Create a tabular data model

·      Be able to use an analysis services tabular data model in an enterprise BI solution         

This Lecture 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 completing this Lecture, you will be able to:

·      Describe the fundamentals of DAX

·      Use DAX to create calculated columns and measures in a tabular data model                

This Lecture 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 completing this Lecture, you will be able to:

·      Describe data mining

·      Use the data mining add‐in for Excel

·      Create a custom data mining solution