Designing Self-Service Business Intelligence and Big Data Solutions (20467)

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About this Course

This five-day instructor-led course teaches students how to design and implement a BI infrastructure. The course discusses design, installation. the course discusses design, installation, and maintenance of a BI platform.

This course maps to skills and knowledge measured by Microsoft Exam 70-467, and in conjunction with on-the-job experience, can help prepare you for the exam.

*This course helps prepare for exam 70-467 in the Expert Level SQL Server 2012 certification track for MCSE- Microsoft Certified Solutions Expert: Business Intelligence

Note: The Beta version of this course (20467AB) utilizes pre-release software in the virtual machine for the labs. Microsoft SQL Server 2012 SP1 CTP4, Microsoft SharePoint Server 2013 Preview, Microsoft Office 2013 Preview, and Microsoft Visio 2013 Preview are used in this course.

Audience Profile

This course is intended for BI professionals such as BI Architects or database professionals who need to design BI solutions. BI Architects are responsible for the overall design of the BI infrastructure, including how it relates to other data systems in use. In addition, their responsibilities include Online Analytical Processing (OLAP) cube design and integration with Microsoft SharePoint or line-of-business applications. Finally, they may apply those skills in a Windows Azure SQL Server database environment.

At Course Completion

After completing this course, students will be able to:

  • Plan the components of a BI solution.
  • Plan a BI infrastructure.
  • Design a data warehouse.
  • Design an ETL solution.
  • Plan analytical data models.
  • Plan a BI delivery solution.
  • Design a Reporting Services solution.
  • Design an Excel reporting solution.
  • Plan a SharePoint Server BI solution.
  • Monitor and optimize a BI solution.
  • Plan for BI operations.

Prerequisites

Before attending this course, students must have:
  • A basic understanding of dimensional modeling (star schema) for data warehouses.
  • The ability to create Integration Services packages that include control flows and data flows.
  • The ability to create a basic multidimensional cube with Analysis Services.
  • The ability to create a basic tabular model with PowerPivot and Analysis Services.
  • The ability to create Reporting Services reports with Report Designer.
  • The ability to implement authentication and permissions in the SQL Server database engine, Analysis Services, and Reporting Services.
  • Familiarity with SharePoint Server and Microsoft Office applications, particularly Excel.
Students who attend this training can meet the prerequisites by attending the following courses, or obtaining equivalent knowledge and skills:
  • 10777A: Implementing a Data Warehouse with Microsoft SQL Server 2012
  • 10778A: Implementing Data Models and Reports with Microsoft SQL Server 2012

Course Outline

Module 1: Introduction to Self-Service Business Intelligence

This module introduces self-service BI.

Lessons

  • Extending Enterprise BI
  • Microsoft Self-Service BI and Big Data Technologies

Lab: Exploring an Enterprise BI Solution

  • Viewing Reports
  • Analyzing Data in a Data Model
  • Analyzing Data from Multiple Sources

After completing this module, you will be able to: Describe ways in which an enterprise BI solution can be extended. Identify Microsoft technologies for self-service BI and Big Data analysis.

Module 2: Self-Service Reporting

This module describes how to use Report Builder as a tool for self-service Microsoft SQL Server Reporting Services report authoring.

Lessons

  • Introduction to Self-Service Reporting
  • Shared Data Sources and Datasets
  • Report Parts

Lab: Implementing Self-Service Reporting

  • Using Report Builder
  • Simplifying Data Access for Business Users
  • Using Report Parts

After completing this module, you will be able to:

  • Support self-service reporting with Report Builder.
  • Create shared data sources and datasets for self-service reporting scenarios.
  • Use report parts as reusable report elements.

Module 3: Self-Service Data Modeling with PowerPivot

This module describes how to use PowerPivot in Microsoft Excel to create self-service data models for analysis.

Lessons

  • Creating Data Models in Excel with PowerPivot
  • Using DAX in a PowerPivot Data Model

Lab: Self-Service Data Modeling with PowerPivot

  • Creating a Data Model with PowerPivot
  • Enhancing a Data Model
  • Extending a Data Model

After completing this module, you will be able to:

  • Use PowerPivot to create tabular data models in Excel.
  • Enhance data models with custom DAX expressions.

Module 4: Importing Data with Power Query

This lesson describes how to use Power Query in Microsoft Excel to find and import data.

Lessons

  • Introduction to Power Query
  • Using Power Query to Import Data

Lab: Using Power Query

  • Importing data with Power Query
  • Merging Queries
  • Adding a Query to a Data Model

After completing this module, you will be able to:

  • Enable Power Query and use it to search for data online
  • Use Power Query to import data from multiple data sources into an Excel data model

Module 5: Visualizing Data with Power View in Microsoft Excel

This module describes how to use Power View in Microsoft Excel to create interactive data visualizations.

Lessons

  • Introduction to Power View
  • Creating Dynamic Data Visualizations

Lab: Visualizing Data with Power View

  • Using Power View

After completing this module, you will be able to:

  • Describe the features of Power View
  • Use Power View to create interactive data visualizations in Excel

Module 6: Visualizing Geographic Data with Power Map

This module describes how to use Power Map in Microsoft Excel to create geographic data visualizations.

Lessons

  • Introduction to Power Map
  • Using Power Map

Lab: Visualizing Geographic Data with Power Map

  • Creating a Power Map Tour
  • Visualizing Data Over Time

After completing this module, you will be able to:

  • Describe the features and usage scenarios of Power Map
  • Use Power Map to create visualizations of geographic data

Module 7: Collaborative BI with Microsoft SharePoint Server

This module describes how to use Microsoft SharePoint Server in an enterprise environment to enable users to share PowerPivot workbooks and Power View reports.

Lessons

  • Sharing PowerPivot Workbooks
  • Managing PowerPivot Services in SharePoint Server
  • Using Power View in SharePoint Server

Lab: Using SharePoint Server for BI Collaboration

  • Sharing a PowerPivot Workbook
  • Managing PowerPivot Data Refresh
  • Using Power View in SharePoint Server

After completing this module, you will be able to:

  • Share a PowerPivot workbooks in SharePoint Server
  • Manage PowerPivot services in SharePoint Server
  • Use Power View to create interactive data visualizations in SharePoint Server

Module 8: The Windows Azure Marketplace Data Market

This module describes how to find and use datasets in the Windows Azure Marketplace.

Lessons

  • Introduction to the Windows Azure Marketplace
  • Using Windows Azure Marketplace Data in Microsoft Excel

Lab: Using the Windows Azure Marketplace

  • Finding Data in the Windows Azure Marketplace
  • Using Windows Azure Marketplace Data in Excel

After completing this module, you will be able to:

  • Find data in the Windows Azure Marketplace
  • Import Windows Azure Marketplace data into Microsoft Excel

Module 9: Cloud Collaboration with Power BI for Microsoft Office 365

This module introduces Power BI for Microsoft Office 365, and describes how to use it for cloud-based, collaborative self-service BI.

Lessons

  • Introduction to Power BI
  • Natural Language Queries with Q&A
  • Sharing Queries
  • The Data Management Gateway

Lab: Using Power BI

  • Provisioning Power BI
  • Viewing Reports and Querying Data in Power BI
  • Sharing Queries
  • Cloud-Enabling a Data Source

After completing this module, you will be able to:

  • Browse reports in a Power BI site
  • Use Q&A to query data in a Power BI site
  • Share Power Query queries with other organizational users
  • Publish on-premises data sources to the cloud

Module 10: Introduction to Big Data and Windows Azure HDInsight

This module introduces Big Data concepts and describes the key features of Windows Azure HDInsight.

Lessons

  • Introduction to Big Data
  • Windows Azure HDInsight

Lab: Using Windows Azure HDInsight

  • Provisioning a Windows Azure HDInsight Cluster
  • Processing Data with HDInsight
  • Analyzing Big Data in Microsoft Excel

After completing this module, you will be able to:

  • Describe key features of Big Data.
  • Use Windows Azure HDInsight to process Map/Reduce jobs

Module 11: Processing Big Data with Pig and Hive

This module introduces Pig and Hive, and describes how you can use them to process Big Data in Windows Azure HDInsight.

Lessons

  • Processing Big Data with Pig
  • Processing Big Data with Hive

Lab: Processing Big Data with Pig and Hive

  • Processing Big Data with Pig
  • Processing Big Data with Hive

After completing this module, you will be able to:

  • Use Pig to process Big Data
  • Use Hive to process Big Data

Module 12: Implementing Big Data Processing Solutions with Windows Azure HDInsight

This module introduces key Windows Azure HDInsight technologies that enable you to design and implement automated, repeatable Big Data processing solutions that support self-service BI.

Lessons

  • Automating Big Data Processing Tasks
  • Integrating Windows Azure HDInsight with Enterprise Data

Lab: Creating a Big Data Solution

  • Using HCatalog to Abstract Storage Locations
  • Using Oozie to Coordinate a Workflow
  • Using Sqoop to Export Data

After completing this module, you will be able to:

  • Design and implement an automated Big Data processing solution
  • Integrate Windows Azure HDInsight with Self-Service BI Solutions