Data Management + Data Cleaning - Best Practices!
Throughout our experience working with a variety of partners on all-things-data, we've picked up some simple tips + tricks along the way. Some of the best practices we use & share with all of our clients are:
- Define goals + important indicators first
This one is huge and goes a long way in making sure you don't gather too much data / make things messy from the very beginning. We dedicated a whole other blog post to this very topic, so read more about it here! - Collect clean data from the start
There are several ways to go about this. Including option choices in your survey (vs. open text fields) promotes consistency in answers / eliminates spelling errors / etc. We also recommend automating where possible using relevancy (i.e. only ask question B if answer to question A is 'yes'). Lastly, taking time to thoroughly train team members conducting the survey leads to increased quality in the data collected. - Review for accuracy as you go
Often times, people wait until the end of a project to realize that the data they collected is full of mistakes, duplicate submissions, etc. By utilizing SDK scripts to automatically remove duplicates & identify outliers, you can transform your raw data into something useful in real time! - Ensure data is easily accessible by your team
SDK dashboards are the perfect way for your team to visualize how your data collection campaign is performing as the project goes on. It can be invaluable for decision making if key players on your team have easy access to what's going on + can make quick sense of complex data.
Questions? Want to learn more? Reach out to us today!
