Visão Geral

O foco deste Curso Microsoft SQL Developing SQL Data Models, é a criação de soluções gerenciadas de BI empresarial. Ele descreve como implementar modelos de dados multidimensionais e tabulares e como criar cubos, dimensões, medidas e grupos de medidas. Este curso ajuda você a se preparar para o Exame 70-768.

Objetivo

Após concluir este Curso Microsoft SQL Developing SQL Data Models, os alunos serão capazes de:

• Descrever os componentes, a arquitetura e a natureza de uma solução de BI
• Criar um banco de dados multidimensional com Analysis Services
• Implementar dimensões em um cubo
• Implementar medidas e grupos de medidas em um cubo
• Usar sintaxe MDX
• Personalizar um cubo
• Implementar um banco de dados tabular
• Use DAX para consultar um modelo tabular
• Use mineração de dados para análise preditiva

Publico Alvo

O público principal deste curso são profissionais de banco de dados que precisam cumprir a função de Desenvolvedor de BI para criar soluções de BI corporativas. As responsabilidades principais incluirão:

• Implementando bancos de dados multidimensionais usando o SQL Server Analysis Services
• Criando modelos de dados semânticos tabulares para análise usando o SQL Server Analysis Services

Pre-Requisitos

Antes de frequentar este curso, os alunos devem ter:

• Experiência de consulta de dados usando Transact-SQL

Conteúdo Programatico

Module 1: Introduction to Business Intelligence and Data Modeling This module introduces key BI concepts and the Microsoft BI product suite. Lessons

• Introduction to Business Intelligence
• The Microsoft business intelligence platform

Lab : Exploring a BI Solution

• Exploring a Data Warehouse
• Exploring a data model

After completing this module, students will be able to:

• Describe BI scenarios, trends, and project roles.
• Describe the products that make up the Microsoft BI platform.

Module 2: Creating Multidimensional Databases This module describes how to create multidimensional databases using SQL Server Analysis Services. Lessons

• Introduction to Multidimensional Analysis
• Data Sources and Data Source Views
• Cubes
• Overview of Cube Security
• Configure SSAS
• Monitoring SSAS

Lab : Creating a multidimensional database

• Creating a Data Source
• Creating and Configuring a data Source View
• Creating and Configuring a Cube
• Adding a Dimension to a Cube

After completing this module, you will be able to:

• Describe considerations for a multidimensional database.
• Create data sources and data source views.
• Create a cube
• Implement security in a multidimensional database.
• Configure SSAS to meet requirements including memory limits, NUMA and disk layout.
• Monitor SSAS performance.

Module 3: Working with Cubes and Dimensions This module describes how to implement dimensions in a cube. Lessons

• Configuring Dimensions
• Defining Attribute Hierarchies
• Implementing Sorting and Grouping Attributes
• Slowly Changing Dimensions

Lab : Working with Cubes and Dimensions

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

After completing this module, you will be able to:

• Configure dimensions.
• Define attribute hierarchies.
• Implement sorting and grouping for attributes.
• Implement slowly changing dimensions.

Module 4: 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 Regular Relationships
• Configuring Measure Group Storage

After completing this module, you will be able to:

• Configure measures.
• Configure measure groups.

Module 5: Introduction to MDX This module 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

• Querying a cube using MDX
• Adding a Calculated Member

After completing this module, you will be able to:

• Use basic MDX functions.
• Use MDX to add calculations to a cube.
• Use MDX to query a cube.

Module 6: Customizing Cube Functionality This module describes how to customize a cube. Lessons

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

Lab : Customizing a Cube

• Implementing an action
• Implementing a perspective
• Implementing a translation

After completing this module, you will be able to:

• Implement KPIs in a Multidimensional database
• Implement Actions in a Multidimensional database
• Implement perspectives in a Multidimensional database
• Implement translations in a Multidimensional database

Module 7: Implementing a Tabular Data Model by Using Analysis Services This module 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 Data Model in an Enterprise BI Solution

Lab : Working with an Analysis Services Tabular Data Model

• Creating an Analysis Services Tabular Data Model
• Configure Relationships and Attributes
• Configuring Data Model for an Enterprise BI Solution.

After completing this module, students will be able to:

• Describe tabular data models
• Describe how to create a tabular data model
• Use an Analysis Services Tabular Model in an enterprise BI solution

Module 8: Introduction to Data Analysis Expression (DAX) This module 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 in a Tabular Data Model

Lab : Creating Calculated Columns and Measures by using DAX

• Creating Calculated Columns
• Creating Measures
• Creating a KPI
• Creating a Parent – Child Hierarchy

After completing this module, students will be able to:

• Describe the key features of DAX
• Create calculated columns and measures by using DAX

Module 9: Performing Predictive Analysis with Data Mining This module describes how to use data mining for predictive analysis. Lessons

• Overview of Data Mining
• Creating a Custom Data Mining Solution
• Validating a Data Mining Model
• Connecting to and Consuming a Data-Mining Model
• Using the Data Mining add-in for Excel

Lab : Using Data Mining

• Creating a Data Mining Structure and Model
• Exploring Data Mining Models
• Validating Data Mining Models
• Consuming a Data Mining Model
• Using the Excel Data Mining add-in

After completing this module, students will be able to:

• Describe considerations for data mining
• Create a data mining model
• Validate a data mining model
• Connect to a data-mining model
• Use the data mining add-in for Excel