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Tag Archives: clean data

FAQ Friday: What does “clean data” mean?

Whenever information is being gathered, there is a potential for problems to crop up with “dirty” data. Extra spaces, misspellings, city names written in ALL CAPS in one data source and Title Case in another, multiple spellings for the same item,

Garbage In, Garbage Out: Why the quality of your data matters more than its speed

Many years ago (I won’t tell you how many), my high school computer science teacher first introduced me to the concept of GIGO. It stands for Garbage In, Garbage Out and what it means is your results are entirely dependent on the quality of your beginnings.

Five more tips for cleaning your data

Last month, we gave you 5 tips for cleaning your data to make sure your data analytics run as smoothly as possible. Today, I’m going to add 5 more tips to help you get your data into great shape.

Dirty Data Is Not Your Friend

Dirty data – it’s not your friend. No, I’m not talking about things that don’t belong in the workplace! I’m talking about informational data sources that have become riddled with misspellings and extra spaces, variations in cases, and three different ways to write the same address.