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Home Courses 204663: SQL Server Analysis Services 2012 (3 day version of course 20466)

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204663: SQL Server Analysis Services 2012 (3 day version of course 20466)

Length: 3    Cost: $1,945 + GST    Version: SQL Server 2012 - 2014

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About this Course

This course has been created for SQL users, who would like to focus on implementing multidimensional databases using analysis services over a 3 day period.

For a more in-depth training course that covers reporting services and analysis services, or if you are working towards certification or have Microsoft software assurance benefits that you would like to utilise for training then the following 5 day course is recommended. 20466: Implementing Data Models and Reports with Microsoft SQL Server 2012-2014.

Please note from 1 April 2017 we will only supply digital courseware, if a hard copy is preferred an additional cost will apply.



Audience


This course is intended for database professionals who need to fulfil a Business Intelligence Developer role to create analysis solutions. Primary responsibilities include:

  • Implementing multidimensional databases by using SQL Server Analysis Services.
  • Creating tabular semantic data models for analysis by using SQL Server Analysis Services.
  • Create data mining solutions by using SQL Server Analysis Services

Prerequisites

Before attending this course, the student should have:

  • 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.

At Course Completion

This course is designed to provide training on how to design and implement multidimensional analysis solutions, create PowerPivot and tabular data models, and discover business insights by using data mining.

After completing this course, participants 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 PowerPivot
  • Use DAX to query a tabular model
  • Implement a Tabular Database
  • Use Data Mining for Predictive Analysis

Course Outline


Module 1: Introduction to Business Intelligence and Data Modelling

This module provides an introduction to Business (BI) Intelligence. It describes common BI scenarios, current trends in BI, and the typical roles that are involved in creating a BI solution. It also introduces the Microsoft BI platform and describes the roles Microsoft SQL Server 2012 and Microsoft SharePoint 2010 play in Microsoft BI solutions.

  • Introduction to Business Intelligence
  • The Microsoft Business Intelligence Platform

Lab : Reporting and Analyzing Data

  • Exploring a Reporting Services Repot
  • Exploring a PowerPivot Workbook
  • Exploring a Power View Report

After completing this module, students will be able to:

  • Describe common BI scenarios and current BI trends.
  • Describe the main technologies that make up the Microsoft BI platform.

Module 2: Creating Multidimensional Databases

The fundamental purpose of using SQL Server Analysis Services online analytical processing (OLAP) solutions is to build cubes that you can use to perform complex queries and return the results in a reasonable time. This module provides an introduction to multidimensional databases and introduces the core components of an OLAP cube.

  • 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

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 Dimensions

In SQL Server Analysis Services, dimensions are a fundamental component of cubes. This module provides an insight into the creation and configuration of dimensions and dimension hierarchies.

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

Lab : Defining Dimensions

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

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

A measure represents a column that contains quantifiable data, usually numeric, that you can aggregate. This module describes measures and measure groups. The module also explains how you can use measures to define fact tables and associate dimensions.

  • Working with Measures
  • Working with Measure Groups

Lab : Configuring Measures and Measure Groups

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

After completing this module, students will be able to:

  • Describe measures.
  • Describe measure groups

Module 5: Introduction to MDX

Multidimensional Expressions (MDX) is the query language that you use to work with and retrieve multidimensional data in SQL Server Analysis Services. This module describes the fundamentals of MDX. It also 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

Lab : Using MDX

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

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

In this module, you will learn how to customize cube functionality by using several technologies available to you in SQL Server Analysis Services. These technology customizations include: Key Performance Indicators, Actions, Perspectives, and Translations.

  • Working with Key Performance Indicators
  • Working with Actions
  • Working with Perspectives
  • Working with Translations

Lab : Customizing a Cube

  • Implementing an Action
  • Implementing a Perspective
  • Implementing a Translation

After completing this module, students will be able to:

  • Describe Key Performance Indicators.
  • Implement Actions.
  • Explain Perspectives.
  • Describe Translations.

Module 7: Implementing a Tabular Data Model with Microsoft PowerPivot

This module introduces tabular data models, explains how to install and use the PowerPivot for Excel add-in, and describes how to share a workbook to PowerPivot Gallery.

  • 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

After completing this module, students will be able to:

  • Describe the key features and benefits of tabular data models and PowerPivot technologies.
  • Create a PowerPivot for Excel workbook.
  • Share a PowerPivot for Excel workbook to PowerPivot Gallery and use a PowerPivot for Excel workbook as a data source.

Module 8: Introduction to DAX

This module covers 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.

  • DAX Fundamentals
  • Using DAX to Create Calculated Column 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

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 an Analysis Services Tabular Data Model

With SQL Server 2012-2014, you can install Analysis Services in Tabular mode and create tabular data models that information workers can access by using tools such as Excel and Power View. This module describes Analysis Services tabular data models and explains how to develop a tabular data model by using the SQL Server Data Tools.

  • Introduction to Analysis Services Tabular Data Model Projects
  • Developing an Analysis Services Tabular Data Model in SQL Server Data Tools

Lab : Working with an Analysis Services Tabular Data Model

  • Creating an Analysis Data Services Tabular Data Model 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 Model
  • Implementing Security in a 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 by Using SQL Server Data Tools.

Module 10: Performing Predictive Analysis with Data Mining

SQL Server Analysis Services includes data mining tools that you can use to identify patterns in your data, helping you to determine why particular things happen and to predict what will happen in the future. 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 Excel, and how to incorporate data mining results into Reporting Services reports.

  • Overview of Data Mining
  • Creating a Data Mining Solution
  • Validating a Data Mining Solution
  • Consuming a Data Mining Solution

Lab : Using Data Mining to Support a Marketing Campaign

  • Using Table Analysis Tools
  • Creating a Data Mining Model
  • Using the Data Mining Add-in for Excel
  • 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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