Every Modern Company Needs a Data Lake — and Most Don’t Have One
A data lake is a simple idea: it is a single place where all of a company’s data is stored so it can be analyzed, combined, and understood across the entire business.
Most companies don’t have one.
Instead, their data is trapped inside dozens of disconnected systems — Stripe for billing, HubSpot for sales, an ERP for finance, product databases, and support tools. Each system holds valuable information, but only within its own data pools. These isolated data pools slowly become stagnant. They can answer small departmental questions, but they can’t power enterprise decisions.
A data lake fixes that.
What Is a Data Lake?
A data lake (often implemented as a cloud-based enterprise data warehouse such as BigQuery, Snowflake, or Redshift) stores raw data from tools like Stripe, HubSpot, QuickBooks, and product databases to be analyzed as a whole. It is the foundation of modern business intelligence, reporting, and revenue analytics.
Think of it like a real lake.
Rain, snow, and glaciers form high in the mountains. They melt and flow downhill through rivers into one large lake. That lake becomes a shared resource that feeds everything downstream.
Your software systems are those mountain sources. ETL pipelines act as rivers, carrying data from Stripe, HubSpot, your ERP, and your product into a single data lake. Once the data arrives, it is no longer restricted to one department. It becomes a full enterprise source of truth.
Instead of many small, stagnant pools, you get one deep, living body of data.
Why a Data Lake Is the Only Way to Get a Full Enterprise Source of Truth for Company Metrics
Without a data lake, companies cannot get an accurate view of MRR, ARR, churn, bookings, or revenue across Stripe and HubSpot.
Sales sees pipeline.
Finance sees cash.
Support sees tickets.
Product sees usage.
But leadership needs the whole picture.
When all data flows into a data lake, it becomes an enterprise source of truth. Metrics line up. Forecasts become reliable. Executives can see what is happening in real time instead of waiting for spreadsheets to be reconciled. This turns your data from a time-wasting project into an asset.
A Real-World Example: Stripe + HubSpot Revenue Reporting
I recently worked with a SaaS company that used Stripe for subscription billing and HubSpot for CRM. Leadership wanted to see their annual recurring revenue (ARR) every day and share it across the company.
Stripe knew who was paying, who was overdue, and who had churned. HubSpot knew who the customers were, what they were sold, and what was in the pipeline. But the two systems couldn’t see each other.
So we built a data lake.
We loaded Stripe and HubSpot into a central enterprise data warehouse. We joined subscriptions to customers and built an enterprise source of truth for MRR, ARR, churn, upsell, and bookings. Those metrics then flowed into dashboards so the entire company aligned in real-time.
When revenue moves, everyone knows.
When goals are close, Slack lights up.
The whole company can rally around the same truth.
That is the power of a data lake.
In Summary
A data lake creates an enterprise source of truth by combining marooned data into an enterprise data warehouse. This enables accurate MRR, ARR, churn, and revenue analytics that can be shared across the entire organization.
Your data already exists.
A data lake lets you finally use it.
Let me help you
I’m Chris Heaton. I have 10 years of enterprise software development experience followed by 15 years leading SaaS companies as a CFO. I know what business leaders need to see — and I know how to build the connectivity that make it possible.
My team at LastMileAutomated helps companies become lean, automated, and data-driven by turning isolated systems into a single, powerful enterprise source of truth.
If you’re ready to stop guessing and start seeing:
chris@lastmileautomated.com
lastmileautomated.com
