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Mar052012

Course 10778 - Implementing Data Models and Reports with Microsoft SQL Server 2012 - New!

Course 10778 - Implementing Data Models and Reports with Microsoft SQL Server 2012 

About this Course

This 5-day instructor-led course describes how to empower information workers through self-service analytics and reporting. Students will learn how to implement PowerPivot and tabular data models, create and deliver rich data visualizations with Power View and SQL Server Reporting Services, and discover business insights by using data mining. This course helps people prepare for exam 70-466.

Audience Profile

The primary audience for this course are database professionals who need to fulfill BI Developer role to create analysis and reporting solutions. Primary responsibilities will include:

  • ·         Implement reporting solutions by using SQL Server Reporting Services
  • ·         Implementing multidimensional databases by using SQL Server Analysis Services
  • ·         Creating tabular semantic data models for analysis by using SQL Server Analysis Services
  • ·         Create visualizations of data by using Power View
  • ·         Create data mining solutions by using SQL Server Analysis Services

In addition to their professional experience, students who attend this training should have technical knowledge equivalent to the following course:

  • ·         10774A: Writing Queries with Microsoft SQL Server Transact-SQL

 

Course Outline

Module 1: Introduction to Business Intelligence and Data Modeling

This module provides an introduction to Business Intelligence (BI). It describes common BI scenarios, current trends in BI, and the typical roles involved in creating a BI solution. It also introduces the Microsoft BI platform, and describes the roles that SQL Server Denali and SharePoint 2010 play in Microsoft BI solutions.

Lessons

  • ·         Introduction to Business Intelligence
  • ·         The Microsoft Business Intelligence Platform

Lab : Reporting and Analyzing Data

  • ·         Exploring a Reporting Services report
  • ·         Exploring a PowerPivot workbook

Describe the key BI concepts and the Microsoft BI product suite.

Module 2: Implementing Reports with Reporting Services

This module describes how to create reports with Reporting Services.

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 : Implementing Reports with Reporting Services

  • ·         Creating a Report
  • ·         Grouping and Aggregating Data in a Report
  • ·         Adding a Chart to a Report
  • ·         Implementing Parameters in a Report
  • ·         Publishing and Viewing a Report
  • ·         Optional Exercise: Creating Visual Comparisons in a Report
  • ·         Optional Exercise:Creating a Map Report

Create reports with Reporting Services.

Module 3: Supporting Self-Service Reporting

This module describes how to create reusable report items that simplify self-service reporting.

Lessons

  • ·         Introduction to Report Builder
  • ·         Creating Reusable Report Items

Lab : Supporting Self-Service Reporting

  • ·         Using Report Builder
  • ·         Creating a shared data source
  • ·         Creating shared data sets
  • ·         Creating a Report Part

Create reusable report items that simplify self-service reporting.

Module 4: Managing a Reporting Infrastructure

Describes how to manage a reporting infrastructure.

Lessons

  • ·         Managing Security
  • ·         Managing Report Execution
  • ·         Delivering Reports with Subscriptions
  • ·         Troubleshooting Reporting Services

Lab : Implementing Report Subscriptions

  • ·         Configuring Report Execution
  • ·         Implementing a Standard Subscription
  • ·         Implementing a Data-Driven Subscription

Manage a reporting infrastructure.

Module 5: Creating Multidimensional Databases

This module provides an introduction to multidimensional databases and introduces the core components of an 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

  • ·         Creating a Data Source
  • ·         Creating and Modifying a Data Source View
  • ·         Creating and Modifying a Cube

Create a multidimensional database with Analysis Services.

Module 6: Working with Cubes and Dimensions

This module describes how to create multidimensional databases and introduces the core components of an OLAP cube

Lessons

  • ·         Configuring Dimensions
  • ·         Defining Attribute Hierarchies
  • ·         Sorting and Grouping Attributes

Lab : Working with Cubes and Dimensions

  • ·         Configuring Dimensions
  • ·         Defining Relationships and Hierarchies
  • ·         Sorting and Grouping Dimension Attributes

Implement dimensions in a cube.

Module 7: 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

  • ·         Configuring Measures
  • ·         Defining Dimension Usage and Relationships
  • ·         Configuring Measure Group Storage

Implement measures and measure groups in a cube.

Module 8: Introduction to MDX

In this module, students will learn the fundamentals of Multidimensional Expressions. Students will also learn about building 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

  • ·         Querying a Cube by Using MDX
  • ·         Creating a Calculated Member

Use MDX Syntax.

Module 9: Customizing Cube Functionality

In this module describes how to customize cube functionality by using several technologies available to you in Microsoft SQL Server Denali Analysis Services.

Lessons

  • ·         Implementing Key Performance Indicators
  • ·         Implementing Actions
  • ·         Implementing Perspectives
  • ·         Implementing Translations

Lab : Customizing a Cube

  • ·         Implementing a KPI
  • ·         Implementing an Action
  • ·         Implementing a Perspective
  • ·         Implementing a Translation

Customize a cube.

Module 10: Implementing a Tabular Data Model by Using Microsoft PowerPivot

This module explains how to install and use the PowerPivot for Excel add-in and the PowerPivot for SharePoint gallery. It also provides an introduction to the concepts underlying these technologies, such as the BI Semantic Model and Tabular Data Models.

Lessons

  • ·         Introduction to Tabular Data Models and PowerPivot Technologies
  • ·         Creating a Tabular Data Model by Using PowerPivot for Excel
  • ·         Sharing a PowerPivot Workbook and Using PowerPivot Gallery

Lab : Using PowerPivot for Excel

  • ·         Creating a Tabular Data Model by Using PowerPivot for Excel
  • ·         Using a Tabular Data Model in Excel
  • ·         Sharing a PowerPivot Workbook to PowerPivot Gallery
  • ·         Using a PowerPivot Workbook as a Data Source

Implement a Tabular Data Model in PowerPivot.

Module 11: Introduction to Data Analysis Expression (DAX)

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 these 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

  • ·         Creating Calculated Columns
  • ·         Creating Measures
  • ·         Using Time Intelligence
  • ·         Creating a Dynamic Measure

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

Module 12: Implementing an Analysis Services Tabular Data Model

This module describes Analysis Services Tabular Data Models and explains how to develop a Tabular Data Model by using the Business Intelligence Development Studio.

Lessons

  • ·         Introduction to Analysis Services Tabular Data Model Projects
  • ·         Implementing an Analysis Services Tabular Data Model in Business Intelligence Development Studio

Lab : Working with an Analysis Services Tabular Data Model

  • ·         Creating an Analysis Services Tabular Data Model Project from a PowerPivot Workbook
  • ·         Implementing a Perspective
  • ·         Implementing Partitions
  • ·         Deploying an Analysis Services Tabular Data Model
  • ·         Enabling Access to a Tabular Data Model
  • ·         Configuring DirectQuery Storage Mode
  • ·         Implementing Security in a Tabular Data Model

Implement a Tabular database.

Module 13: Creating Data Visualizations With Power View

This module describes how to use Power View to create interactive data visualizations.

Lessons

  • ·         Introduction to Power View
  • ·         Visualizing Data with Power View

Lab : Creating Interactive Reports with Power View

  • ·         Modify the Tabular Data Model
  • ·         Create a Simple Power View Report
  • ·         Interactive Visualizations
  • ·         Create a Scatter Chart and a Play Axis

Use Power View to create interactive data visualizations.

Module 14: Performing Predictive Analysis with Data Mining

The 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 a and Consuming a Data-Mining Model

Lab : Performing Predictive Analysis with Data Mining

  • ·         Using the Excel Data Mining Add-In
  • ·         Creating a Data Mining Structure and Model
  • ·         Exploring Data Mining Models
  • ·         Validating Data Mining Models
  • ·         Consuming a Data Mining Model

Use Data Mining for Predictive Analysis.

 

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