{
    "action": "final",
    "content": "**What it is:** This is a log of Indian startup funding deals, in the table `raw.startup_funding` (3,044 rows, 14 columns). It looks like observational data, with each row recording a funding event as it was reported.\n\n**What one row represents:** One reported funding deal, meaning one startup receiving money from one or more investors on a given date. The key is `Sr No`. The sample rows I pulled show the fields that describe a deal:\n- `Date dd/mm/yyyy`: when the deal was reported, e.g. 09/01/2020.\n- `Startup Name`: the company, e.g. BYJU'S, Shuttl, Mamaearth, Zomato. Some entries are a URL instead of a name (row 4 is `https://www.wealthbucket.in/`).\n- `Industry Vertical`: the sector, e.g. E-Tech, Transportation, FinTech, Logistics.\n- `City  Location`: the startup's city, e.g. Bengaluru, Gurgaon, Mumbai, Chennai, Pune.\n- `Investors Name`: the investor(s) behind the round, e.g. Tiger Global Management, Sequoia Capital India.\n- `InvestmentnType`: the round type, e.g. Seed Round, Series A, Series B, Series C, Private Equity Round, Pre-series A.\n- `Amount in USD`: the deal size.\n\nThe table also has `SubVertical` and `Remarks`, plus ingestion metadata columns (`_ingestion_timestamp`, `_batch_id`, `_source_file`, `_source_system`).\n\n**Things to watch:**\n- `Amount in USD` is stored as text. It uses Indian digit grouping, e.g. `20,00,00,000` is 200 million, and `80,48,394` is about 8.0 million. It needs cleaning before it can be summed or averaged.\n- `Date dd/mm/yyyy` is also text, in day/month/year format.\n- Labels are inconsistent. The card lists roughly 903 distinct industry verticals and 66 distinct investment types, which suggests many near-duplicate spellings.\n\n**What it's useful for:** Looking at deal volume and size by sector, city, investor and round type, and at whether funding is speeding up or slowing down over time. These are the questions the dataset serves for investors, founders and ecosystem analysts.\n\nThese descriptions come from the 8 sample rows (the query behind step-0) and the dataset card. I haven't yet computed any full-table statistics."
}