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Schema: aptos.price Table: fact_prices_ohlc_hourly Type: View

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What

A comprehensive fact table holding id and provider specific open, high, low, close hourly prices, from multiple providers. This data set includes raw, non-transformed data coming directly from the provider APIs and rows are not intended to be unique. As a result, there may be data quality issues persisting in the APIs that flow through to this fact based model. If you are interested in using a curated data set instead, please utilize ez_prices_hourly.

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Columns

Column NameData TypeDescription
ASSET_IDTEXTThe unique identifier representing the asset.
HOURTIMESTAMP_NTZHour that the price was recorded at.
OPENFLOATOpening price of the recorded hour in USD.
HIGHFLOATHighest price of the recorded hour in USD
LOWFLOATLowest price of the recorded hour in USD
CLOSEFLOATClosing price of the recorded hour in USD
PROVIDERTEXTPROVIDER column
INSERTED_TIMESTAMPTIMESTAMP_NTZThe UTC timestamp when the row was inserted into the table, representing when the data was first recorded. Data type: Timestamp Example: 2024-01-15 14:30:25.123456 Business Context: Essential for data lineage tracking and insertion timing analysis. Critical for understanding data freshness and processing delays. Enables data quality analysis and processing performance monitoring.
MODIFIED_TIMESTAMPTIMESTAMP_NTZThe UTC timestamp when the row was last modified, representing when the data was most recently updated. Data type: Timestamp Example: 2024-01-15 14:30:25.123456 Business Context: Essential for data freshness analysis and update tracking. Critical for understanding data modification patterns and change frequency. Enables data quality monitoring and update performance analysis.
FACT_PRICES_OHLC_HOURLY_IDTEXTThe unique primary key identifier for each row in the table, ensuring data integrity and uniqueness. Data type: String Example: 0x1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef Business Context: Essential for data integrity and unique row identification. Critical for join operations and data relationship management. Enables precise data retrieval and referential integrity maintenance.