```json {"action": "final", "content": "Based on the dataset's schema and metadata, here are the columns present across the monthly funding tables, their data types, and what each represents:\n\n### Core Business Columns\n* **`Company Name`** (`VARCHAR`): The name of the startup receiving the funding.\n* **`Founded`** (`BIGINT` / `VARCHAR`): The year the startup was established (stored as an integer in most tables, but as text in the May 2022 table).\n* **`Location`** (`VARCHAR`): The city or region where the startup is headquartered.\n* **`Sector`** (`VARCHAR`): The industry or market category the startup operates in (e.g., FinTech, EdTech, E-commerce).\n* **`What it does`** (`VARCHAR`): A brief description of the startup's core product, service, or business model.\n* **`Founders`** (`VARCHAR`): The name(s) of the individual(s) who founded the company.\n* **`Investor`** (`VARCHAR`): The venture capital firm(s), angel investor(s), or entity providing the capital for the funding round.\n* **`Amount`** (`VARCHAR`): The total funding amount raised in the round. Because it is stored as text, it typically contains currency symbols (like `$`), formatting, or terms like \"Undisclosed\".\n* **`Stage`** (`VARCHAR`): The maturity stage of the funding round (e.g., Seed, Pre-series A, Series B, Debt Financing).\n\n### System & Metadata Columns\nThese columns are automatically generated during the data ingestion process to track data lineage:\n* **`_ingestion_timestamp`** (`TIMESTAMP`): The exact date and time when the record was loaded into the database.\n* **`_batch_id`** (`VARCHAR`): A unique identifier for the specific data load job that processed the record.\n* **`_source_file`** (`VARCHAR`): The name of the original file from which the row was extracted.\n* **`_source_system`** (`VARCHAR`): The name of the system or pipeline that provided the data."} ```