Implementing Data Models and Reports with SQL Server 2014 (20466D)
Note: 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.
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.
This course requires that you meet the following prerequisites:
- At least 2 years’ experience of working with relational databases, including:
- Designing a normalized database.
- Creating tables and relationships.
- Querying with Transact-SQL.
- Some basic knowledge of data warehouse schema topology (including star and snowflake schemas).
- 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.
After completing this course, students will be able to:
- Describe the components, architecture, and nature of a BI solution.
- Create a multidimensional database with Analysis Services.
- Implement dimensions in a cube.
- Implement measures and measure groups in a cube.
- Use MDX Syntax.
- Customize a cube.
- Implement a Tabular Data Model in SQL Server Analysis Services.
- Use DAX to enhance a tabular model.
- Create reports with Reporting Services.
- Enhance reports with charts and parameters.
- Manage report execution and delivery.
- Implement a dashboard in SharePoint Server with PerformancePoint Services.
- Use Data Mining for Predictive Analysis.
Module 1: Introduction to Business Intelligence and Data Modeling
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.
- Introduction to Business Intelligence
- The Microsoft Enterprise BI Platform
Module 2: Creating Multidimensional Databases
This module provides an introduction to multidimensional databases and introduces the core components of an Online Analytical Processing (OLAP) cube.
- Introduction to Multidimensional Analysis
- Creating Data Sources and Data Source Views
- Creating a Cube
- Overview of Cube Security
Module 3: Working with Cubes and Dimensions
This module describes how to create and configure dimensions and dimension hierarchies in an Analysis Services multidimensional data model.
- Configuring Dimensions
- Defining Attribute Hierarchies
- Sorting and Grouping Hierarchies
Module 4: Working with Measures and Measure Groups
This module describes measures and measure groups. It also explains how you can use them to define fact tables and associate dimensions with measures.
- Working with Measures
- Working with Measure Groups
Module 5: Introduction to MDX
This module describes the fundamentals of MDX and explains how to build calculations, such as calculated members and named sets.
- MDX Fundamentals
- Adding Calculations to a Cube
- Using MDX to Query a Cube
Module 6: Customizing Cube Functionality
This module describes how to enhance a cube with Key Performance Indicators (KPIs), actions, perspectives, and translations.
- Implementing Key Performance Indicators
- Implementing Actions
- Implementing Perspectives
- Implementing Translations
Module 7: Implementing an Analysis Services Tabular Data Model
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.
- Introduction to Tabular Data Models
- Creating a Tabular Data Model
- Using an Analysis Services Tabular Data Model in an Enterprise BI Solution
Module 8: 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 them in your tabular data models.
- DAX Fundamentals
- Using DAX to Create calculated Columns and Measures in a Tabular Data Model
Module 9: Implementing Reports with SQL Server Reporting Services
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.
- Introduction to Reporting Services
- Creating a Report with Report Designer
- Grouping and Aggregating Data in a Report
- Showing Data Graphically
- Filtering Reports Using Parameters
Module 10: Automating Report Execution and Delivery
This module describes how to apply security and report execution settings, and how to create subscriptions to deliver reports.
- Managing Report Security
- Managing Report Execution
- Delivering Reports with Subscriptions and Data Alerts
- Troubleshooting Reporting Services
Module 11: Delivering BI with SharePoint PerformancePoint Services
This module introduces Microsoft SharePoint Server as a platform for BI, and then focuses on building BI dashboards and scorecards with PerformancePoint Services.
- Introduction to SharePoint Server as a BI Platform
- Planning Security for a SharePoint Server BI Solution
- Planning for PerformancePoint Services
Module 12: Performing Predictive Analysis with Data Mining
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.
- 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