Product

Bring supported databases, files, and saved datasets into one visual workflow. Prepare your data, reuse the results, schedule recurring work, and compare saved versions.

See the full roadmap →

01 · Connect

Start with the data your team uses

Choose a supported database connection, upload CSV or Excel files, or reuse a saved dataset. Preview the data before building your preparation steps.

Choose your starting point

How you connect

Connections

Save, test, and manage supported database connections your workflows and imports can reuse — credentials encrypted at rest.

Input

Bring a saved dataset or supported database source onto the canvas, then reuse that input across your preparation steps.

Import Wizard

Bring a spreadsheet or supported database source into DataQloo as a reusable dataset, with column profiling before you commit.

02 · Transform

Prepare it any way you need

Clean, combine, and reshape data without writing scripts.

Core transformations

FilterSummarizeSort

Expanding continuously

FormulaCleanReplaceSampleJoinUnionLookupAppendBranchGroup ByDeduplicateFuzzy MatchPivotUnpivotWindowRankSQLSub-WorkflowAI TransformPython

Available transformations, in depth

Filter

Narrows a dataset down to the rows that matter with a single condition — equals, contains, greater than, in a list, and more.

Summarize

Groups and aggregates rows — SUM, COUNT, AVG, MIN, MAX, and COUNT DISTINCT — to turn raw rows into a business-readable metric.

Sort

Orders results by a column, ascending or descending, so the most relevant rows surface first.

03 · Reuse

Build once. Reuse it every time the data changes.

Save a workflow’s result as a reusable dataset — the input to another workflow, or a table you rerun in one click instead of rebuilding from scratch. This is one of DataQloo’s biggest differences from a one-off script: the workflow itself is the reusable asset.

Output

The terminal node that saves a workflow's results as a reusable Platform Dataset, so it can be used as the Input to another workflow.

Browse

A terminal node that previews your workflow's results — the table, inferred schema, column profile, generated SQL, and any configuration messages, all in one panel.

04 · Automate

Keep recurring reports on schedule

Run saved workflows hourly, daily, or weekly in your chosen timezone. Monitor runs in Automation, then pause, resume, or run a schedule immediately when needed. Schedule frequency and allowances follow your workspace plan. See the scheduling guide for setup and monitoring.

Roles & Permissions

Workspace-scoped role-based access control — workspace admin, member, and viewer roles govern who can do what across connections, datasets, and settings.

For data engineering teams: a lot of engineering time goes to fulfilling one-off requests — “filter this by region,” “total this by month.” DataQloo lets teammates build those requests themselves on the canvas, against a connection your team controls, with the underlying query visible to review if you want to. It's not a replacement for your orchestration layer or existing ETL pipelines — see DataQloo vs. Airflow.

05 · Insights

Understand your prepared datasets

Profile row counts, missing values, duplicates, and column ranges. Compare the profiles of two saved versions to see what changed. Available features depend on your workspace plan.

Read about dataset versions →

06 · AI

Planned

Use AI once your data is connected and trusted

Describe what you want to transform, review the suggested workflow, and approve before anything runs. Nothing executes without you. Not built yet.

See the roadmap →