Data Hygiene Checklist | Page 2
Step 1: Assess the issue.
You need to know how bad it is before you can fix the problem. Check your database to
see how much data is missing and how many variants there are in the system. There are
some great tools to help you audit your database, including Kickbox and NetProspex
Data HealthScan .
Step 2: Clean up what's there.
Always clean up the existing records in your system before putting new filters and
controls in place. SHARE THIS! If you're missing a lot of data, consider using a data
connector that consolidates data from different sources and fills in the blank values. If the
same data is getting recorded in different variations, consider normalizing the data—a
process that converts multiple variations to a single, "normal" version.
Step 3: Consult before deleting.
Before deleting any bad records, check the salespeople who own them. Merging records
is always preferable to deleting: remember how much hard work it took to collect that
data in the first place!
Step 4: Normalize your fields.
Now that your existing data is clean and tidy, you can put practices in place to keep new
data clean. Start by replacing regular fields with normalized fields that automatically
convert variations to a single version of the data. For example, whether users type "US,"
"U.S.A.," or "America," a normalized field converts the content into a single standard of
your choice.
Step 5: Use picklists where possible.
Picklists—field forms that offer a list of predetermined values—are ideal for capturing
data about people's industries, areas of interest, job titles, roles, regions and many other
types of demographic or firmographic information. By limiting the amount of free-form
data entry users can input, you can limit the number of errors significantly.
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Clean data starts here
How can you ensure your data is supporting rather than undermining your success? The following
eight-point checklist for the care and feeding of your database will help to take it from mean to clean.