Case Study: Trumid achieves self-service BI and near-real-time analytics with AtScale

Trumid Realizes Self Service BI and Near Real Time Data Analytics with AtScale

Trumid, a Forbes-recognized FinTech handling about $2 billion in daily transactions, faced slow, extract-driven analytics that prevented same‑day decision making. Stakeholders depended on the data team to build models, reports were inconsistent, and the company wanted self‑service Looker analytics in near real time—so they engaged AtScale and its semantic layer to address these challenges.

Trumid implemented a new stack (BigQuery + dbt, Looker) with AtScale’s semantic layer between BI and the data warehouse to centralize models, pre‑aggregate data, and expose business‑friendly metrics. AtScale reduced latency from one day to around one hour, enabled non‑technical users to create dashboards and ad‑hoc analyses with consistent numbers, and freed data engineers from repetitive ETL/dashboard work so they can focus on machine learning and higher‑value projects.

Trumid

Chris Reid

Senior Data Engineer