DatriseAI-first ETL

Polygon Stock API to Looker Studio Integration

AI-first ETL from Polygon Stock API into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Polygon Stock API into Looker Studio

Datrise syncs Polygon Stock API's tickers, aggregate bars, trades, quotes, splits, and dividends into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Polygon Stock API: Equities market data, trades, and aggregates.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Polygon Stock API entities map to Looker Studio

Polygon Stock API entityLooker Studio objectNotes
tickerspolygon_stock_api_tickersid PK · custom fields → flattened columns for chart fields
aggregate barspolygon_stock_api_aggregate_barsid PK · linked to polygon_stock_api_tickers
tradespolygon_stock_api_tradesid PK · linked to polygon_stock_api_tickers
quotespolygon_stock_api_quotesid PK · linked to polygon_stock_api_tickers

FAQ

How does Datrise handle Polygon Stock API's custom fields in Looker Studio?

Flexible values are stored as flattened columns for chart fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker Studio types.

How does the Polygon Stock API to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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