Microsoft Power BI: Advanced Data Analysis and Visualisation


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About This Course

Power BI is quickly gaining popularity among professionals in data science as a cloud-based service that helps them easily visualize and share insights from their organizations' data.

In this data science course, you will learn from the Power BI product team at Microsoft with a series of short, lecture-based videos, complete with demos, quizzes, and hands-on labs. You’ll walk through Power BI, end to end, starting from how to connect to and import your data, author reports using Power BI Desktop, and publish those reports to the Power BI service. Plus, learn to create dashboards and share with business users—on the web and on mobile devices.

What you'll learn

  • Connect, import, shape, and transform data for business intelligence (BI)
  • Visualize data, author reports, and schedule automated refresh of your reports
  • Create and share dashboards based on reports in Power BI desktop and Excel
  • Use natural language queries
  • Create real-time dashboards

Please Note: Learners who successfully complete this course can earn a CloudSwyft digital certificate and skill badge - these are detailed, secure and blockchain authenticated credentials that profile the knowledge and skills you’ve acquired in this course.

prerequisites

Some experience in working with data from Excel, databases, or text files.

Course Syllabus

Week 1
  • Understanding key concepts in business intelligence, data analysis, and data visualization
  • Importing your data and automatically creating dashboards from services such as Marketo, Salesforce, and Google Analytics
  • Connecting to and importing your data, then shaping and transforming that data
  • Enriching your data with business calculations
Week 2
  • Visualizing your data and authoring reports
  • Scheduling automated refresh of your reports
  • Creating dashboards based on reports and natural language queries
  • Sharing dashboards across your organization
  • Consuming dashboards in mobile apps
Week 3
  • Leveraging your Excel reports within Power BI
  • Creating custom visualizations that you can use in dashboards and reports
  • Collaborating within groups to author reports and dashboards
  • Sharing dashboards effectively based on your organization’s needs
Week 4
  • Exploring live connections to data with Power BI
  • Connecting directly to SQL Azure, HD Spark, and SQL Server Analysis Services
  • Introduction to Power BI Development API
  • Leveraging custom visuals in Power BI

Meet the instructors

Will Thompson

Will Thompson

Program Manager, Power BI
Microsoft

Will is a self-confessed data geek, working his way through sysadmin and DBA roles before joining Microsoft. He spent 5 years helping customers in the UK implement and get value out of Microsoft's BI solution. When an opportunity arose to move into the engineering world he jumped at it, and now helps translate customer and market requirements into new features as a Program Manager in the Power BI team.

Jonathan Sanito

Jonathan Sanito

Senior Content Developer
Microsoft

Jonathan works as a content developer and project manager for Microsoft focusing in Data and Analytics online training. He has worked with trainings for developer and IT pro audiences, from Microsoft Dynamics NAV to Windows Active Directory. Before coming to Microsoft, Jonathan worked as a consultant for a Microsoft partner, implementing Microsoft Dynamics NAV solutions.

Kim Manis

Kim Manis

Program Manager
Microsoft

Kim is a program manager on the Power BI Desktop team, working to make data analysis fun and easy. Before that, Kim has worked on all sorts of products ranging from productivity software, social networks and online retail. In her spare time she loves exploring the Pacific Northwest, cooking and finding the perfect animated gif.

Miguel Llopis

Miguel Llopis

Senior Program Manager
Microsoft

Miguel Llopis is a Senior Program Manager specialized on Data Connectivity for Power BI.

  1. Course Number

    DAT207x
  2. Classes Start

  3. Classes End

  4. Estimated Effort

    Total 12 to 24 hours
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