Data & Analysis
Inspect experiment tables, build visualizations, and export datasets.
After mobile or IoT data is processed, each experiment exposes data tables on the web platform. Start by checking the rows and their context; then visualize or export the table that answers your research question.
Choose a task
- Writing analysis macros — transform
a triggering measurement, read earlier workbook values through
ctx, and return named values for later cells and processing. - Viewing your data — switch between data tables, sort and filter rows, inspect values, annotate rows, and create saved visualizations.
- Exporting data — create a background export in CSV, NDJSON, JSON Array, Parquet, or Excel format and download it when ready.
- Advanced: Databricks notebooks — understand where notebooks fit and how to frame an advanced analysis request. There is no self-service notebook launcher in the researcher interface.
Programmatic access through user API keys is intentionally not documented yet. The API-key implementation is still an unmerged draft, so the shipped guide does not promise a control that is absent from this branch.
Mobile's Export measurements action creates a local JSON backup. It is different from a web dataset export, which operates on a processed experiment table and offers several analysis formats.
If a recent upload is not visible, first confirm that it is Synced in the mobile app. Processing may continue after broker acknowledgement; the live pass must establish the normal delay before this guide promises one.