Data Agent serves as the data source for Analytics Agent. Together they form a collect → prepare → present pipeline: Data Agent regularly collects data and shapes it into one consistent form, while Analytics Agent builds reports, charts and dashboards on top. Each product does its own part, and both run on your server.
How it works
Data Agent scripts export data to Parquet — that is the raw data, the source of truth. Then the load.py script builds it into a single SQLite database — this is the database Analytics Agent uses for visualization. The Parquet stays beside it: the data can always be verified against it without touching the database.
Reading is separated from writing
Analytics Agent works with Data Agent’s data read-only: it builds reports, charts and dashboards on the ready databases, and queries never change them — the data can be viewed, not damaged. The analyst never edits the databases or the raw files directly.
When a report needs to be added, fixed or extended — a missing column, say, or a weekly recalculation — Analytics Agent does not touch the files itself: it hands the work to Data Agent through its protected API (key access, every call verified). Through that API it puts or replaces a script, runs it, refreshes the data and sets a schedule when needed — Data Agent validates and does everything itself. Fresh data appears, and the store stays in order.
What you need to do
- Ask the agent in chat to collect the data you need — it will create the source, the scripts and run them.
- After the
load.pyrun, the database appears in the Lakehouse and the source registers automatically (how — on the Data Sources page). - In Analytics Agent, connect that source — see the Data Sources section of its documentation — and build reports and charts.
Example: the demo pipeline
Data Agent ships with a demonstration pipeline — a Forex market data simulator: the forex-simulator/api folder with extract.py and load.py. After a run, the forex-simulator_api.sqlite database appears in the Lakehouse — a ready example of what Analytics Agent receives: sources, schemas, tables.
Consistency rules
- Parquet is always the source of truth: the raw data is never rebuilt;
- SQLite is the derived database: rebuilt on every run, so it always matches the latest raw data;
- a README next to the database describes it: where the data comes from, the structure, the fields — Analytics Agent and a human read the data the same way;
- only Data Agent changes the data: Analytics Agent reads the ready databases and hands every addition or fix through its protected API, where each call is verified.
The analysis templates in Analytics Agent work through the same pairing (a library of 257 ready-made solutions: forecasts, segments, scoring, anomalies): the agent adapts their scripts to your data and runs them on Data Agent through its API. Details in the Analysis Templates section.
More about Analytics Agent’s capabilities is on the Analytics Agent page.
See also: Lakehouse, Data Sources.