Why a Warehouse
One source of truth.
The Spreadsheet Ceiling
For years, marketers stitched reports together in spreadsheets: export from Google Ads, export from Meta, paste, VLOOKUP, repeat. It works until it doesn't. Row limits, broken formulas, and stale data make weekly reporting a chore that eats analyst time.
A data warehouse breaks that ceiling. It is a central, query-optimized database where every channel's data lands, gets joined, and stays fresh, ready for analysis at any scale.
What a Warehouse Actually Is
A cloud data warehouse like BigQuery or Snowflake is a managed, columnar database built for analytics, not transactions. It separates storage from compute, so you can store terabytes cheaply and only pay for the queries you run.
Columnar storage means a query that touches 3 of 50 columns reads only those 3, scanning far less data. That is why an aggregate over a billion ad-click rows can return in seconds.
Transactional DB (OLTP) vs Warehouse (OLAP)
row-oriented column-oriented
many small writes few huge reads
normalized denormalized / star
MySQL, Postgres BigQuery, Snowflake