Microsoft Business Intelligence (MSBI) Certification 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

·      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

·      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

·      Deploying SSIS Projects

·      Planning SSIS Package Execution

·      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

·      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

·      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

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

·      Validate a data mining solution

·      Connect to and consume a data mining solution

·   As a SQL Server database professional, you may be required to participate in, or perhaps even lead, a project with the aim of implementing an effective enterprise BI solution. Therefore, it is important that you have a good understanding of the various elements that comprise a BI solution, the business and IT personnel typically involved in a BI project, and the Microsoft products that you can use to implement the solution.

·   Lessons

·   Introduction to Business Intelligence

·   The Microsoft Enterprise BI Platform

·   Lab : Exploring a BI Solution

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

·   Describe the elements of a typical BI solution.

·   Select appropriate Microsoft technologies for a BI solution.

·   Describe key considerations for planning a BI project.

·   This module provides an introduction to multidimensional databases and introduces the core components of an Online Analytical Processing (OLAP) cube.

·   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 completing this module, you will be able to:

·   Describe the considerations for a multidimensional database.

·   Create data sources and data source views.

·   Create a cube.

·   Implement security in a multidimensional database.

·   This module describes how to create and configure dimensions and dimension hierarchies in an Analysis Services multidimensional data model.

·   Lessons

·   Configuring Dimensions

·   Defining Attribute Hierarchies

·   Sorting and Grouping Hierarchies

·   Lab : Working with Cubes and Dimensions

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

·   Configure dimensions.

·   Define attribute hierarchies.

·   Sort and group attributes.

·   This module describes measures and measure groups. It also explains how you can use them to define fact tables and associate dimensions with measures.

·   Lessons

·   Working with Measures

·   Working with Measure Groups

·   Lab : Configuring Measures and Measure Groups

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

·   Configure measures.

·   Configure measure groups.

·   This module describes the fundamentals of MDX and explains how to build calculations, such as calculated members and named sets.

·   Lessons

·   MDX Fundamentals

·   Adding Calculations to a Cube

·   Using MDX to Query a Cube

·   Lab : Using MDX

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

·   Describe MDX.

·   Add calculations to a cube.

·   Describe how to use MDX in client applications.

·   This module describes how to enhance a cube with Key Performance Indicators (KPIs), actions, perspectives, and translations.

·   Lessons

·   Implementing Key Performance Indicators

·   Implementing Actions

·   Implementing Perspectives

·   Implementing Translations

·   Lab : Customizing a Cube

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

·   Implement Key Performance Indicators.

·   Implement Actions.

·   Implement Perspectives.

·   Implement Translations.

·   This module describes Analysis Services tabular data models and explains how to develop a tabular data model using the SQL Server Data Tools for Business Intelligence (BI) add-in for Visual Studio.

·   Lessons

·   Introduction to Tabular Data Models

·   Creating a Tabular Data Model

·   Using an Analysis Services Tabular Data Model in an Enterprise BI Solution

·   Lab : Implementing an Analysis Services Tabular Data Model

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

·   Describe Analysis Services tabular data model projects.

·   Implement an Analysis Services tabular data model.

·   Use an Analysis Services tabular data model.

·   This module explains the fundamentals of the DAX language. It also explains how you can use DAX to create calculated columns and measures, and how you can use them in your tabular data models.

·   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 module, you will be able to:

·   Describe the fundamentals of DAX.

·   Use DAX to create calculated columns and measures.

·   This module introduces Microsoft SQL Server Reporting Services and discusses the tools and techniques that a professional BI developer can use to create and publish reports.

·   Lessons

·   Introduction to Reporting Services

·   Creating a Report with Report Designer

·   Grouping and Aggregating Data in a Report

·   Showing Data Graphically

·   Filtering Reports Using Parameters

·   Lab : Creating a Report with Report Designer

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

·   Describe the key features of Reporting Services.

·   Use Report Designer to create a report.

·   Group and aggregate data in a report.

·   Publish and view a report.

·   This module describes how to apply security and report execution settings, and how to create subscriptions to deliver reports.

·   Lessons

·   Managing Report Security

·   Managing Report Execution

·   Delivering Reports with Subscriptions and Data Alerts

·   Troubleshooting Reporting Services

·   Lab : Implementing Report Subscriptions

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

·   Configure security settings for a report server.

·   Configure report execution settings to optimize performance.

·   Use subscriptions and alerts to automate report and data delivery.

·   Troubleshoot reporting issues.

·   This module introduces Microsoft SharePoint Server as a platform for BI, and then focuses on building BI dashboards and scorecards with PerformancePoint Services.

·   Lessons

·   Introduction to SharePoint Server as a BI Platform

·   Planning Security for a SharePoint Server BI Solution

·   Planning for PerformancePoint Services

·   Lab : Implementing PerformancePoint Services

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

·   Describe SharePoint Server as a BI platform.

·   Use PerformancePoint Services to deliver BI functionality.

·   Configure PerformancePoint Data Sources.

·   Create Reports, Scorecards, and Dashboards.

·   This module introduces data mining, describes how to create a data mining solution, how to validate data mining models, how to use the Data Mining Add-ins for Microsoft Excel, and how to incorporate data mining results into Reporting Services reports.

·   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 Data Mining Data

·   Lab : Using Data Mining to Support a Marketing Campaign

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

·   Describe the key data mining concepts and use the Data Mining Add-ins for Excel.

·   Create a data mining solution.

·   Validate data mining models.

·   Use data mining data in a report.