Your product data lives in the warehouse. Your customer data lives everywhere else.

This is the identity resolution problem, and it's the single biggest blocker for SaaS analytics. Your product database identifies users by email or internal UUID. Salesforce tracks contacts and accounts with its own IDs. Stripe knows customers by payment method. Intercom uses yet another identifier. When your VP of CS asks "which accounts are at risk of churn based on usage drop-off," the answer requires joining four systems that have no shared key. Every time someone does this in a spreadsheet, they lose edge cases — trial users who converted, accounts that merged, contacts who changed companies. The fix is a persistent identity layer in your warehouse that maps every system's ID to a canonical account and user.

Your product team can tell you exactly how many API calls Account X made last month. Your revenue team can tell you exactly what Account X pays and when they renew. Neither team can answer: "Do accounts that use Feature Y at least 3x/week expand at a higher rate than accounts that don't?" That question — which directly drives product and GTM strategy — requires joining product events to Salesforce opportunities to Stripe invoices. It's a 3-system join that nobody has time to build manually, so the question goes unanswered and decisions get made on gut feel instead of data.

This problem compounds quarterly. Marketing reports 200 MQLs. Sales says they only received 140 qualified leads. CS says 30 new accounts onboarded. The CFO sees three numbers and asks which one is real. The answer is all three are "real" within their own system, but the definitions don't match: marketing counts form fills, sales counts opportunities that passed qualification, CS counts accounts that completed onboarding. Until these definitions are reconciled in a warehouse — with one funnel model from first touch to active customer — every leadership meeting starts with 20 minutes of arguing about whose numbers are right.