Access Pattern Analyzer
Upload a file-access log — user, file, timestamp — to see which files get used most, peak activity hours, and per-user breakdowns.
How to use Access Pattern Analyzer
- Start by providing the required input: Drop a CSV with user, file, and timestamp columns. Use Load Sample to try example data first.
- No additional settings need to be configured.
- Run the tool with Most Accessed Files or Per-User Activity or Peak Hours.
- Review the result or preview on the page and confirm it matches your input before using or sharing it.
Turning a raw access log into "who's actually using what"
Most file-access logs are plain, unreadable rows of timestamps and usernames that nobody looks at until something goes wrong. Aggregating the same data by most-accessed files, peak hours, and per-user activity turns it into something you'd actually check periodically — to see which documents are genuinely in active use versus quietly forgotten.
Spotting usage patterns a spreadsheet filter would miss
Peak-hour breakdowns in particular are hard to eyeball in raw log form but immediately obvious once grouped — a sudden concentration of activity at 2am, for instance, is worth noticing even before you know whether it's benign.
What columns does my CSV need?
A user column, a file column, and a timestamp column — common header name variants are matched automatically.
Is this the same as anomaly detection?
No — this tool summarizes normal usage patterns. For flagging unusual or suspicious activity specifically, use the Access Anomaly Detector instead.
How many access events can this handle?
Processing happens in your browser, so very large logs (hundreds of thousands of rows) will take longer, but there's no hard row limit.