{
    "slots": [
        {
            "scope": "dataset",
            "slot": "nature",
            "value": {
                "nature": "observational"
            },
            "evidence": {
                "reasoning": "Kaggle export of publicly reported Indian startup funding deals. The consumer of this data does not operate the funding process; it records outside investment events."
            }
        },
        {
            "scope": "dataset",
            "slot": "decisions_served",
            "value": {
                "decisions": [
                    "Which industry verticals or sub-verticals to target or prioritize for investment or product focus based on deal volume and amount over time",
                    "Which cities to prioritize for launching a startup, opening an office, or sourcing deals",
                    "Which investors to approach for a given stage, sector, or city based on their past deals",
                    "Which funding round type (angel, seed, Series A/B/C, private equity) is typical for a sector, to benchmark a raise",
                    "How much to raise or what valuation to expect, based on historical ticket sizes by vertical and round",
                    "Whether funding activity is accelerating or slowing, to time a fundraise or market entry"
                ]
            },
            "evidence": {
                "reasoning": "The table has one row per funding deal, with date, vertical, city, investor, investment type and amount. These dimensions support sector, geography, investor and round-type analysis."
            }
        },
        {
            "scope": "dataset",
            "slot": "levers",
            "value": {
                "levers": []
            },
            "evidence": {
                "reasoning": "The data records third-party funding events reported publicly. No operator here controls these deals, so no lever is measured. Investor, sector and city are outcomes, not controllable inputs."
            }
        },
        {
            "scope": "dataset",
            "slot": "audience",
            "value": {
                "audience": [
                    "venture capital and angel investors",
                    "startup founders",
                    "market and ecosystem analysts",
                    "policy makers and startup-ecosystem researchers"
                ]
            }
        },
        {
            "scope": "table:startup_funding",
            "slot": "role",
            "value": {
                "role": "fact"
            },
            "evidence": {
                "reasoning": "Each row is a funding event with a monetary measure and a date."
            }
        },
        {
            "scope": "table:startup_funding",
            "slot": "grain",
            "value": {
                "unit": "one row per reported funding deal (startup, date, investor(s), amount)",
                "key_columns": [
                    "Sr No"
                ]
            },
            "evidence": {
                "reasoning": "Sr No is a unique sequential key. Startup names repeat (2459 unique across 3044 rows), consistent with multiple rounds per startup."
            }
        },
        {
            "scope": "table:startup_funding",
            "slot": "temporal_posture",
            "value": {
                "posture": "event-dated, stored as text in dd/mm/yyyy; plus a constant ingestion timestamp",
                "columns": [
                    "Date dd/mm/yyyy",
                    "_ingestion_timestamp"
                ]
            },
            "evidence": {
                "reasoning": "The deal date is a varchar and needs parsing before time analysis. _ingestion_timestamp has a single value and is load metadata, not event time."
            }
        },
        {
            "scope": "table:startup_funding",
            "slot": "column_bindings",
            "value": {
                "bindings": [
                    {
                        "column": "Sr No",
                        "binding": "identifier"
                    },
                    {
                        "column": "Date dd/mm/yyyy",
                        "binding": "temporal"
                    },
                    {
                        "column": "Startup Name",
                        "binding": "identifier"
                    },
                    {
                        "column": "Industry Vertical",
                        "binding": "category"
                    },
                    {
                        "column": "SubVertical",
                        "binding": "category"
                    },
                    {
                        "column": "City  Location",
                        "binding": "category"
                    },
                    {
                        "column": "Investors Name",
                        "binding": "category"
                    },
                    {
                        "column": "InvestmentnType",
                        "binding": "category"
                    },
                    {
                        "column": "Amount in USD",
                        "binding": "measure"
                    },
                    {
                        "column": "Remarks",
                        "binding": "category"
                    },
                    {
                        "column": "_ingestion_timestamp",
                        "binding": "temporal"
                    },
                    {
                        "column": "_batch_id",
                        "binding": "category"
                    },
                    {
                        "column": "_source_file",
                        "binding": "category"
                    },
                    {
                        "column": "_source_system",
                        "binding": "category"
                    }
                ]
            },
            "evidence": {
                "reasoning": "Startup Name is an entity key, since startups repeat across rounds, so it is rebound from category to identifier. SubVertical is free-text and high-cardinality but still categorical. Other bindings follow the derived ones."
            }
        },
        {
            "scope": "table:startup_funding",
            "slot": "derived_measures",
            "value": {
                "measures": [
                    {
                        "column": "Amount in USD",
                        "derived_from": [
                            "Amount in USD"
                        ],
                        "rule": "Stored as text with comma separators in mixed Indian (1,00,00,000) and Western (1,000,000) grouping, sometimes with a trailing comma. Strip commas and cast to number before summing or averaging."
                    }
                ]
            },
            "evidence": {
                "reasoning": "Sample values show inconsistent digit grouping and a trailing comma, so the column is not directly numeric."
            }
        }
    ]
}