Using Power BI to Automate Data Cleaning and

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Using Power BI to Automate Data Cleaning and

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Description: Using Power BI to Automate Data Cleaning and Visualization Chris Urban Assistant Director of Data Analytics Planning Analysis Frederick Burrack Director of Assessment Office of Assessment Visualizing Data through Interactive Reports in

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slide1. Using Power BI to Automate Data Cleaning and Visualization 
slide2. Chris Urban
Assistant Director of Data Analytics
Planning & Analysis Frederick Burrack
Director of Assessment
Office of Assessment 
slide3. Visualizing Data through Interactive Reports in Power BI 
slide4. Data Dashboards 
slide7. Relational Data Modeling 
slide8. Facts Contains fields to break down a Fact Table Dimensions Contains items you want to identify: Sum, average, count, etc. 
slide9. Long and narrow Duplicated Short and wide Unduplicated Facts Dimensions 
slide10. Facts FactResponses[StudentID] Dimensions DimStudent[StudentID] Dimensions relate to Facts.
Used as a filter via Key Fields. 
slide11. Dimensions that surround a
Fact Table are called a “Star Schema” 
slide12. Automating Data Processes 
slide13. Power BI Suite Query and Report Creation Power BI Desktop Power BI Service Power BI Gateways Your Institution’s Data ACCESS PUBLISH Adapted from Microsoft.com 
slide14. Step-by-Step Demonstration 
slide19. An Introduction to DAX Data Analysis Expressions 
slide20. Data Analysis Expressions (DAX) Functions used to create reusable measures that analyze data
Basic commands such as COUNT, SUM, AVERAGE, etc.
Generally used in Fact tables to aggregate
Can reference other DAX formulas – no need to re-enter data 
slide21. Count Responses = COUNT(FactResponses[Response]) Name of the Measure Function Table used to calculate Column Used to Calculate A Basic Measure using DAX 
slide22. Count Responses = COUNT(FactResponses[Response]) 
slide23. Count All Responses = CALCULATE([Count Responses], ALL(DimResponse)) 
slide24. %Responses = [Count Responses] / [Count All Responses] 
slide25. Step-by-Step Demonstration 
slide26. DAX Measures to count Responses Count Responses = COUNT(FactResponses[Response]) Count All Responses = CALCULATE([Count Responses], ALL(DimResponse)) %Responses = [Count Responses] / [Count All Responses] 
slide27. DAX Measures to count students Count Students = DISTINCTCOUNT(FactResponses[student id]) Count All Students = CALCULATE([Count Students], ALL(DimStudent)) %Students = [Count Students] / [Count All Students] 
slide28. Publishing and Sharing Query and Report Creation Power BI Desktop Power BI Service Power BI Gateways Your Institution’s Data ACCESS PUBLISH Adapted from Microsoft.com 
slide30. Sharing Options 
slide31. Request a Pro License ($25/user/yr):https://www.k-state.edu/its/software/software-licenses/ms-power-bi/ 
slide32. K-State Power BI Users Groupemail Chuck Gould – chuck@ksu.edu K-State Power BI Slack Channel
ksupowerbi.slack.com 
slide33. What about the data warehouse? 
slide34. Resource Documents 
slide35. Questions & Discussion Using Power BI to Automate Data Cleaning and Visualization Thanks for coming!

Using Power BI to Automate Data Cleaning and

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