```json { "action": "final", "content": "Here are the columns in the `startup_funding` dataset, along with their data types and what each represents:\n\n### Core Data Columns\n* **`Sr No`** (`BIGINT`): A serial number acting as a unique identifier for each funding record.\n* **`Date dd/mm/yyyy`** (`VARCHAR`): The date the funding deal was announced or took place.\n* **`Startup Name`** (`VARCHAR`): The name of the startup that received the funding.\n* **`Industry Vertical`** (`VARCHAR`): The broad industry category or sector the startup operates in (e.g., E-Commerce, Technology).\n* **`SubVertical`** (`VARCHAR`): A more specific sub-category describing the startup's exact focus or niche.\n* **`City Location`** (`VARCHAR`): The city or geographic location where the startup is based.\n* **`Investors Name`** (`VARCHAR`): The name(s) of the investor(s), venture capital firm(s), or angel(s) who provided the funding.\n* **`InvestmentnType`** (`VARCHAR`): The stage or type of the investment round (e.g., Seed Funding, Private Equity, Series A).\n* **`Amount in USD`** (`VARCHAR`): The total funding amount raised in the round, expressed in US Dollars. *(Note: Stored as text, so it may contain commas or \"unknown\" values that need cleaning before math operations).* \n* **`Remarks`** (`VARCHAR`): Additional notes, context, or remarks regarding the funding deal.\n\n### System Metadata Columns\nThese columns are automatically generated during data ingestion and are generally used for auditing rather than analysis:\n* **`_ingestion_timestamp`** (`TIMESTAMP`): The exact date and time the record was loaded into the database.\n* **`_batch_id`** (`VARCHAR`): An identifier for the specific data load batch.\n* **`_source_file`** (`VARCHAR`): The file path from which the data was ingested.\n* **`_source_system`** (`VARCHAR`): The system or method used to ingest the data (e.g., API)." } ```