Teach DataTug what columns mean

Map query result columns to MeaningGraph entities and fields, so later results show what each column means and the mapping is shared with the project.

Column meaningsAvailable

The problem

When two databases call the same thing by different names, how does anyone know they match?

CustomerID in one database and customer_ref in another may be the same thing, or not. That knowledge lives in people’s heads, so every new query has to rediscover it.

A clearer workflow

Map a column
Pick a result column and map it to an existing MeaningGraph entity and field, or create a new one.
See it in results
Mapped columns show their meaning in later query results, so readers can inspect what a value represents.
Keep it with the project
Meanings are saved as project definitions in its repository, ready for review like any other change.

Worked example

Browse the demo project’s meanings

Starting question

Which columns of the demo project already have a declared meaning?

Steps to follow

Follow “Browse the meanings” to open the demo project’s Meanings. The public project is read-only.
Filter for Customer to see which columns map to the Customer entity, such as ID, Email, FirstName and LastName.
To add or change meanings, copy the demo project to your own GitHub account and edit them there.

What you learn

You see which columns carry a declared meaning and the repository revision each mapping comes from.

Browse the meanings

What changes

What one person learned about a column becomes visible to everyone who queries it.

The case of order 11045 · Act 7 · Teach

In the demo story

Maya maps the Shipping request to its current routing, so Related now finds the link the investigation was missing.

The guided demo of this story is being built. The worked example above runs in today’s demo project.