The DataQloo Team

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.

Data Profiling Isn't Optional: What We Check Before You Build a Workflow

Fill rate, distinct counts, distributions — the questions worth asking about a dataset before you trust a report built on top of it.

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.

PostgreSQL Data Types, and How DataQloo Infers Them

A column's declared PostgreSQL type is only half the story. Here's how DataQloo's Schema tab infers the more useful, semantic type underneath.

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.

"Coming Soon" Means Coming Soon: Why Our Roadmap Is Public

Every unfinished feature on this site is labeled, not hidden. Here's why we built it that way from the start.

Why We Show You the SQL: A Case Against Black-Box Data Tools

A visual canvas that hides what it's actually running is asking for blind trust. We think that's the wrong default.