Openbridge

Stop waiting on ad‑hoc exports and brittle scripts. With Openbridge, you pick the sources you care about—Seller Central, Instagram Stories, Facebook, Amazon Ads, Google Ads, and more—then choose a warehouse you control. Authenticate, select the metrics and dimensions you need, and set a refresh schedule. Openbridge pulls the data, normalizes it, and lands it in your cloud account (Redshift, Athena, BigQuery, Azure Data Lake, or Snowflake) without you writing a line of code. Marketers can move from login credentials to a live, queryable dataset in under an hour, ready for dashboards or ad‑hoc SQL.

For campaign reporting, start by creating a workspace for paid media. Add connectors for Amazon Ads, Google Ads, and Facebook. Use field mapping to standardize naming (campaign, ad group, impressions, clicks, spend, revenue). Apply filters to exclude tests or paused entities. Schedule daily syncs at dawn so dashboards are current for morning standups. Next, define lightweight transformations: calculate ROAS/ACoS, attribute orders by date, and blend organic versus paid outcomes. Version these steps so changes are safe to roll back. When it’s ready, point Looker, Tableau, or Power BI at your warehouse and publish a cross‑channel scorecard that anyone on the team can refresh.

Ecommerce and operations teams can merge marketplace data with inventory and pricing. In one flow, ingest orders and fees from Seller Central, product catalogs from your ERP, and ad spend from Amazon Ads. Use matching rules to reconcile SKUs, deduplicate records, and enrich orders with margin fields. Set data quality gates that quarantine bad rows (missing SKUs, negative prices) and send alerts to Slack or email. If a partner can only deliver flat files, enable managed transfers to pick up CSVs over SFTP or HTTP and automatically load them into the same schemas. Every step is logged, auditable, and recoverable—handy for month‑end close and compliance reviews.

Data engineers can extend pipelines with APIs and automation. Trigger downstream jobs when fresh data lands, push notifications via webhooks, or hand off to dbt for modeling. Configure partitioning and incremental loads to keep large tables fast and cost‑efficient. Maintain a metadata catalog, track lineage from source to report, and promote changes from dev to prod with version history. Typical outcomes: faster creative testing using Instagram Stories engagement, daily marketplace P&L by SKU, multi‑touch performance views across Google and Facebook, and forecasting inputs for supply planning—all powered by datasets that live securely in your cloud.