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Schema: aptos.price Table: dim_asset_metadata Type: View A comprehensive dimensional table holding asset metadata and other relevant details pertaining to each id, 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 dimensional model. If you are interested in using a curated data set instead, please utilize ez_asset_metadata.

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Columns

Column NameData TypeDescription
TOKEN_ADDRESSTEXTThe specific address representing the asset on a specific platform. This will be NULL if referring to a native asset.
ASSET_IDTEXTThe unique identifier representing the asset.
SYMBOLTEXTThe symbol of asset.
NAMETEXTThe name of asset.
PROVIDERTEXTThe provider or source of the data.
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_TIMESTAMP | TIMESTAMP_NTZ | The 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. | | DIM_ASSET_METADATA_ID | TEXT | The 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. |