Declared type vs. semantic type
PostgreSQL will tell you a column is text or numeric. That's accurate, but not always useful — a text column might hold email addresses, phone numbers, or UUIDs, and a numeric column might really be a currency value that shouldn't be averaged the same way a raw count would.
What the Schema tab shows
Every workflow's Schema tab infers a more specific, semantic type per column: Integer, Decimal, Currency, Date, Timestamp, UUID, JSON, Email, Phone, URL, Boolean, or Text — alongside a confidence score and a handful of sample values, so you can sanity-check the inference yourself rather than trusting it blindly.
Why this matters for building a workflow
Knowing a column is semantically a Currency value, not just a generic Decimal, changes how you'd reasonably use it in a Summarize node — summing it makes sense; averaging a UUID doesn't, even though both might be stored as text at the database level. The inference is a hint, not a guarantee — it's computed client-side from the returned result rows, and the confidence score is there because it can be wrong, particularly on small samples.
Where this runs
Type inference happens in two places: the Import Wizard's preview step, before you commit to saving a dataset, and the Schema tab of any workflow's results panel. Both use the same underlying logic, so what you see during import is consistent with what you'll see later when building a workflow against that dataset.
Worth knowing
Type inference is a client-side convenience — it doesn't change your PostgreSQL schema or write anything back to your database.
Related reading
PostgreSQL vs. MySQL for Analytical Workflows
Both are solid relational databases. Here's how they actually differ for the kind of filtering and aggregation work a visual workflow tool does.
Building a Filtered Revenue Report Without Writing SQL
A walkthrough of building a real workflow — connect, filter, summarize, sort — on the canvas, and what the compiled SQL looks like underneath.
How DataQloo Compiles a Visual Workflow Into SQL
Every node you drag onto the canvas becomes part of a single parameterized query. Here's what that compilation step actually does.
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