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Microsoft® Excel® Power Tools

Understanding and Using Excel Power Query and Power Pivot

Continuing Education Credits: CEU: 0.3 

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For data crunchers using Microsoft Excel and Power BI, Excel Power Tools such as Power Query and Power Pivot are invaluable. Frequent users of VLOOKUP and PivotTables, won’t want to miss this 3.5-hour interactive learning session. Saving hours of work each week, Power Query connects data technologies allowing users to discover, combine and refine multiple data sources to meet analysis needs. Power Pivot uses its own language know as Data Analysis Expressions (DAX) to create sophisticated data models allowing complex calculations to be carried out across different tables of data with ease.

With Excel Power Query, data from different sources is cleaned, split and merged to new tables in Excel. Excel Power Pivot comes into play when the capabilities of regular Pivot tables in Excel are exhausted. With Power Pivot, users define how data in each table is related. Learn how Power Query and Power Pivot mastery can take the grunt work out of the daily grind and restore hours previously lost to rigorous data labor and analysis.

What You'll Learn

  • Understand the building blocks of a data model.
  • Determine the best practices for building a data model.
  • Gain insight on how to import data into the data model.
  • Review and understand complex relationships, hierarchies, aggregations and connections.
  • Master the four essential steps in building a Power Query.
  • Glean the knowledge to reshape your data to answer almost any question with Power Query.
  • Use the basics of Data Analysis Expressions (DAX) language for more complex calculations.
  • How calculations work in a Power Pivot and ways to adjust Power Pivots on the fly.
  • Methods for automating built-in Excel data cleanup tools.

Who Will Benefit

This course is for all Excel users, regardless of iOS or PC platform. A basic to intermediate knowledge of formulas and functions, charts, dashboards, PivotTables, Pivot Charts, Relational databases, sparklines and conditional formatting is recommended.