Formatting (data)
Standardising data into a consistent shape before it enters a downstream system. Examples: converting dates from DD/MM/YYYY to YYYY-MM-DD, normalising phone numbers to E.164 format, capitalising names. Prevents downstream validation errors.
Expert insight
Formatting differences (a phone number stored as "+44 20 1234 5678" in one system and "02012345678" in another) look like a trivial fix but multiply across every workflow that moves that field between the two systems. Normalizing formats at the point of entry, not repeatedly downstream in every workflow, avoids fixing the same formatting mismatch a dozen times.
How PURIST uses this
This concept is built into every automation we deploy.
When PURIST builds your automation, Formatting (data) is not an optional consideration it is part of the production standard. Our workflows are tested against edge cases, monitored 24/7, and built to handle what happens when things don't go as expected.
Every client workflow we deploy in the Data category is designed with this principle in mind from day one not added as an afterthought.
Complexity level
Anyone can understand this no technical background needed.
Related terms
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