BI · BIGQUERY · AUTOMATED REPORTING
You don't pay for a screen. You pay for decisions that arrive on time.
A dashboard is the visible surface. The real deliverable is a reliable data layer on BigQuery, plus a report that writes itself and lands in the inbox of the person who never logs in.
Why most dashboards die after a month
Because they're built as screens, not as systems.
The numbers live in five tools that don't talk: the CRM, the ticketing, the telephony, a spreadsheet and someone's memory. So every Friday a human consolidates an Excel by hand, the report arrives late, and nobody fully trusts the figures it contains.
A pretty dashboard on top of broken data doesn't fix that. It decorates it. The decisions still arrive late, and late decisions are the most expensive kind.
Our approach: the data layer first, the screen second
We start where the value lives, where nobody sees it: ingestion from your CRM, ticketing, telephony and business APIs, centralized in BigQuery, with modeled and cleaned pipelines that make reporting error-free instead of a manual export.
Then the visible layer: real-time dashboards with the data viz that matters, alerts on the thresholds you care about, and an automated weekly or monthly report pushed by email or Slack with zero human hands. Infrastructure cost is billed as transparent pass-through, never hidden in our margin. And the whole layer is yours, documented.
What you get
- A centralized data layer on BigQuery: ingestion from CRM, ticketing, telephony and business APIs.
- Modeled, cleaned pipelines that make reporting error-free, not a manual Excel export.
- Real-time dashboards with the data viz that matters, plus alerts on your thresholds.
- An automated weekly or monthly report, pushed by email or Slack with zero human hands.
- Infrastructure cost (BigQuery and friends) billed as transparent pass-through, never hidden in our margin.
Typical use cases
Stack as proof
A dashboard with no data layer underneath is a gauge with nothing behind the glass. We build the capability, not just the screen.
Proof: a reporting loop for a European telecom operator
For Onoff Telecom, our team wired automated customer support to a real-time BigQuery dashboard and a weekly report generated with zero human hands. The agent handles the case, the automation logs it, the dashboard makes it visible, and the report closes the loop.
- A large share of repetitive requests handled without a human, on the order of 50 to 70%estimate, to be confirmed
- First response on common requests cut from hours to about a minuteestimate, to be confirmed
Delivered by our team through its European experience (Evolution Agency, France). Shown here to demonstrate capability, not as a Revolution Agency engagement.
Read the Onoff Telecom caseQuestions we hear before every build
Do we need a data team for this?
No. We build and run the pipelines, and we hand you a documented layer your team can query. If you later hire a data person, they inherit a clean system instead of a pile of exports.
What does the infrastructure cost?
At typical volumes, less than most people expect, and you see every cent: BigQuery and related costs are billed as pass-through, separate from our fee. No surprise line items hidden in our margin.
Can it alert us instead of us checking the dashboard?
Yes, that's the point. Thresholds you define trigger alerts by email or Slack, and the recurring report lands in the inbox of the person who never logs in. The dashboard is there when you want to dig.
Find out if your data layer is the fastest win
The free AI audit maps your sources and tells you what a reliable reporting loop would change, with honest numbers.