Excel Business Intelligence: Power Pivot and DAX

  • Course details

    Data Analysis Expressions (DAX) allow Microsoft Excel users to create powerful calculated fields in Power Pivot. In this course—the third and final installment of the Excel Business Intelligence series—experienced Excel trainer Chris Dutton spells out how to use the DAX language and Power Pivot to explore and analyze relational data models. Chris picks up where he left off in the previous installment of the series, demonstrating how to add calculated columns and measures to data models in Excel. He highlights the differences between calculated columns and DAX measures, covers common DAX formulas and functions, and discusses best practices for working with DAX and Power Pivot.

    Instructor

    • Click here to view Chris Dutton’s instructor page

      Chris Dutton

      Founder & COO, Maven Analytics

      Chris Dutton is a certified Excel MOS Expert, edtech entrepreneur, and best-selling instructor.

      Chris has spent 10+ years specializing in data visualization and business intelligence. As founder and COO of Maven Analytics, Chris' work has been featured by Microsoft, HuffPost, Entrepreneur.com, and the New York Times, reaching more than 500,000 students around the world. A leader in analytics education, Maven Analytics seeks to empower everyday people to change the world with data. Chris graduated summa cum laude and received the Charles G. Bluhdorn Prize in Economics at Tufts University.

    Skills covered in this course

    For each course you will get

    • Exercise files and quizzes
    • Certificate of completion from LinkedIn
    • Offline and audio-only options
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  • Welcome

    - [Chris] Hey everyone. Chris Dutton here, and welcome to Excel Business Intelligence Part 3: Power Pivot and DAX. In this part of the course we'll practice using Power Pivot and Data Analysis Expressions, known as DAX, to explore and analyze the data model that we built in part two. We'll add some powerful calculated columns and measures to our model and practice working with some of the most powerful DAX tools like statistical functions, logical operators, text and filter formulas, and time intelligence. Keep in mind that this is part three of a three-part series, so we'll be picking up right where we left off from part two, which covered Data Modeling 101. Make sure to either work through sections one and two first or download the completed part two project file so that you can follow along from here. We have a lot to cover, so let's dive in.

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