{
    "action": "final",
    "content": "**Size:** The dataset has one table, `raw.AI_Usage_and_Impact_on_Students_and_Professionals`, with **300 rows** and **23 columns**. The row count comes from my queries (step-0 and step-1). The column count comes from the dataset card. The 23 columns include 4 ingestion/metadata fields: `_ingestion_timestamp`, `_batch_id`, `_source_file` and `_source_system`.\n\n**Users:** The 300 rows hold only **288 distinct `User_ID` values**, so some IDs repeat. The card says the grain is one row per surveyed user, so those repeats are worth checking as possible duplicates.\n\n**Time period:** The dataset has **no real time period**. It contains no date or time column for when users answered the survey or used the tools. The only timestamp is `_ingestion_timestamp`, and it has a single value for every row: 2026-10-02 09:58:27. All rows also come from one batch and one source file. That timestamp only shows when the data was loaded, so it can't support any trend or time-based analysis. The data is effectively a single cross-sectional snapshot."
}