Most analytics teams hit the same wall: data lives everywhere. Customer records in Postgres, financials in a spreadsheet, behavioral data in a data warehouse. Joining them means either long engineering cycles or fragile ad-hoc scripts. The result? Analysts spend more time moving and cleaning data than analyzing it.
September 29, 2025
AI Technology
Philipp Buschhaus
7 min.
Traditional BI tools typically assume a single clean source. The moment you need to cross-analyze Postgres tables with spreadsheet data or mix data warehouse facts with operational logs, you end up writing glue code. That often means:
These approaches are slow, brittle, and distract from the actual business question.
To solve this, we built a multi-source query engine directly into Milo. It lets you run a single SQL-like query across heterogeneous data sources, without standing up a separate ETL pipeline.
Here’s how it works under the hood:
The result is fast, efficient, persistent queries across multiple data sources, without writing Python unless you want to.
The new query engine is part of a broader toolkit. Milo dynamically decides the best approach depending on the problem:
By switching intelligently between these three modes, Milo balances speed, flexibility, and reliability.
For data teams and business users, the implications are big:
Modern businesses rarely have a single source of truth. The ability to query across sources efficiently, without building fragile pipelines, is becoming a baseline requirement.
Milo’s query engine makes multi-source analytics as simple as writing a Prompt. Combine Postgres with spreadsheets, or join CRM data from your warehouse with operational logs, all inside one prompt. When data is clean, Milo uses SQL. When it’s messy, it switches to Python. And when you need cross-source joins, the new query engine takes over.
It’s the shortest path from data everywhere to answers anywhere.
If you found this article useful, imagine what Milo could do for your business. Our team will walk you through a personalized demo.