Course 20466-D: Implementing Data Models and Reports with SQL Server 2014

Microsoft

Course 20466-D: Implementing Data Models and Reports with SQL Server 2014

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The focus of this five-day instructor-led course is on creating managed enterprise BI solutions. It describes how to implement multidimensional and tabular data models, deliver reports with Microsoft® SQL Server® Reporting Services, create dashboards with Microsoft SharePoint Server PerformancePoint Services, and discover business insights by using data mining.

This course is designed for customers who are interested in learning SQL Server 2012 or SQL Server 2014. It covers the new features in SQL Server 2014, but also the important capabilities across the SQL Server data platform.

Audience Profile

This course is intended for database professionals who need to fulfill a Business Intelligence Developer role to create analysis and reporting solutions. Primary responsibilities include: implementing analytical data models, such as OLAP cubes, implementing reports, and managing report delivery, creating business performance dashboards, supporting data mining and predictive analysis.

Prerequisites

Course outline

Module 1: Introduction to Business Intelligence and Data Modeling

Module Overview

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 Sessions

Exploring a BI Solution

Lab Lessons

Exploring the Data Warehouse
Exploring the Analysis Services Data Model
Exploring Reports

After completing this module, students 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.

Module 2: Creating Multidimensional Databases

Module Overview

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 Sessions

Creating a Multidimensional Database

Lab Lessons

Creating a Data Source
Creating and Modifying a Data Source View
Creating and Modifying a Cube
Adding a Dimension

After completing this module, students 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.

Module 3: Working with Cubes and Dimensions

Module Overview

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 Sessions

Working with Cubes and Dimensions

Lab Lessons

Configuring Dimensions and Attributes
Creating Hierarchies
Create a Hierarchy with Attribute Relationships
Creating a Ragged Hierarchy
Browse Dimensions and Hierarchies in a Cube

After completing this module, students will be able to:

Configure dimensions.
Define attribute hierarchies.
Sort and group attributes.

Module 4: Working with Measures and Measure Groups

Module Overview

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 Sessions

Configuring Measures and Measure Groups

Lab Lessons

Configuring Measures
Defining a Regular Relationship
Configuring Measure Group Storage

After completing this module, students will be able to:

Configure measures.
Configure measure groups.

Module 5: Introduction to MDX

Module Overview

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 Sessions

Using MDX

Lab Lessons

Creating Calculated Members
Querying a Cube by Using MDX

After completing this module, students will be able to:

Describe MDX.
Add calculations to a cube.
Describe how to use MDX in client applications.

Module 6: Customizing Cube Functionality

Module Overview

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 Sessions

Customizing a Cube

Lab Lessons

Implementing an Action
Implementing Perspectives
Implementing a Translation

After completing this module, students will be able to:

Implement Key Performance Indicators.
Implement Actions.
Implement Perspectives.
Implement Translations.

Module 7: Implementing an Analysis Services Tabular Data Model

Module Overview

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 Sessions

Implementing an Analysis Services Tabular Data Model

Lab Lessons

Creating an Analysis Services Tabular Data Model Project
Configuring Columns and Relationships
Deploying an Analysis Services Tabular Data Model

After completing this module, students 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.

Module 8: Introduction to Data Analysis Expression (DAX)

Module Overview

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 Sessions

Creating Calculated Columns and Measures by using DAX

Lab Lessons

Creating Calculated Columns
Creating Measures
Creating a KPI
Implementing a Parent-Child Hierarchy

After completing this module, students will be able to:

Describe the fundamentals of DAX.
Use DAX to create calculated columns and measures.

Module 9: Implementing Reports with SQL Server Reporting Services

Module Overview

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 Sessions

Creating a Report with Report Designer

Lab Lessons

Creating a Report
Grouping and Aggregating Data
Publishing a Report

After completing this module, students 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.

Module 10: Automating Report Execution and Delivery

Module Overview

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 Sessions

Implementing Report Subscriptions

Lab Lessons

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

After completing this module, students 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.

Module 11: Delivering BI with SharePoint PerformancePoint Services

Module Overview

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 Sessions

Implementing PerformancePoint Services

Lab Lessons

Creating a SharePoint Server Site for BI
Configuring PerformancePoint Data Access
Creating PerformancePoint Reports
Creating a PerformancePoint Scorecard
Creating a PerformancePoint Dashboard

After completing this module, students 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.

Module 12: Performing Predictive Analysis with Data Mining

Module Overview

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 Sessions

Using Data Mining to Support a Marketing Campaign

Lab Lessons

Using Table Analysis Tools
Creating a Data Mining Structure
Adding a Data Mining Model to a Data Mining Structure
Validating Data Mining Models
Using a Data Mining Model in a Report

After completing this module, students 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.

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