20768 – Developing SQL Data Models

A Distancia

On demand

It describes how to implement both multidimensional and tabular data models and how to create cubes, dimensions, measures, and measure groups. This course helps you prepare for the Exam 70-768.
Perfil del usuario objetivo
The primary audience for this course are database professionals who need to fulfil BI Developer role to create enterprise BI solutions.
Primary responsibilities will  include:
• Implementing multidimensional databases by using SQL Server Analysis Services
• Creating tabular semantic data models for analysis by using SQL Server Analysis Services

Duration

24 hs

Al finalizar el curso

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 database
Use DAX to query a tabular model
Use data mining for predictive analysis

Course Outline

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
Creating Data Sources and Data Source Views
Creating a Cube
Overview of Cube Security
Configure SSAS
Monitoring SSAS
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, 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
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 Dimension Usage and 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
Creating 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
Introduction to Business Intelligence
The 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
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

Requisitos previos

Before attending this course, students must have:
Experience of querying data using Transact-SQL

Ver calendario

6 septiembre, 2017

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