Problem / Solution
When looking at data and trying to determine meaningful trends it is helpful to remove any outlier data, so the reports and graphs depict an accurate picture. In this tip, Tim Smith shows us how to use a SQL Server stored procedure to analyze the data and remove any outliers from the dataset. We will look at a sample dataset and the expected results by using averages and standard deviations to determine the outliers for the dataset.
Key Learning Items
- Why tracking outliers is important and how it can affect our data.
- How to remove outliers from a data set, by building a table without outliers.
Read Companion Tip
Tim consults for FinTek Development and teaches the course Automating ETL on Udemy. He’s worked with technology since high school, helping his school win its first TCEA award and continues to work in automation, data architecture, back-end development, and smart contract architecture. Tim enjoys testing new technologies early in the diffusion of innovation curve and was an early adopter of NoSQL and smart contract development. He has a blog at http://www.fintekdev.com/ and helps contribute to local technical and financial events in Texas.
