Leverage Outlier Analysis in Dundas BI to Increase Data Accuracy

Outliers can cause serious problems when you are trying to analyze your data due to their ability to skew a scale or hide trends. Learn how to use interquartile range computations in Dundas BI to help you work with outliers by either hiding or removing them.

For more content on using formulas in Dundas BI, make sure to check out the following videos:

About the Author

Jeff Hainsworth

Jeff Hainsworth is a Senior Solutions Architect at Dundas Data Visualization with over a decade and a half of experience in Business Intelligence. He has a passion for building, coding and everything visual – you know, shiny things! Check out "Off the Charts... with Jeff", his platform for great content on all things analytics, data visualizations, dashboards, and business intelligence. There’s something for everyone!