Data pipelines that keep flowing.
Collection, ETL, event streaming, and scraping — built to run unattended, monitored so failures surface before your customers notice, and operated by us long after launch day.
It starts when nobody trusts the numbers.
Nobody trusts the numbers
The weekly report exists, but it is stitched together by hand from three systems, and two departments quietly keep their own version. Every meeting starts with an argument about whose figure is right.
The scraper someone built once
Market prices, competitor listings, supplier catalogues — gathered by a script a contractor wrote years ago, or by a person with a browser and a long afternoon. When it breaks, it breaks silently, and you find out from a stale report.
The platform bill keeps climbing
Storage and infrastructure costs grow every month, and nobody can say which part of the data estate earns its keep. The system was assembled over years; no one wants to touch it.
You need to move, but you cannot stop
The old system has to be replaced or migrated, but the business runs through it every day. A weekend of downtime is not an option, so the problem gets deferred another quarter.
Pipelines we have built and run.
Replacing a messaging backbone that kept failing
A global telco and media group ran critical flows through a messaging system that could not be relied on, with no real recovery plan behind it. We replaced it with a Kafka event-streaming backbone built for the load it actually carries.
Outcome: roughly £250k a month saved — about £3M a year — plus the disaster recovery the old setup never had.
Customer data at enterprise scale
We migrated a customer-data platform to a managed database service, re-modelling flat storage buckets into domain-aware scopes and collections so the data finally matched the business it described. Separately, we delivered the cloud infrastructure behind a migration of over 250 million customer accounts.
Outcome: around £500k a year cut from platform running costs, and a 250M+ account migration completed with zero service disruption.
Watching an entire luxury-goods market
For a luxury-goods market, we built a full-catalogue price-mapping pipeline: scheduled scraping of retail and grey-market sources, ETL to reconcile them, and a generated report at the end.
Outcome: a standing view of the whole market's pricing, produced on schedule instead of assembled by hand.
Start small, decide with something real in hand.
The first slice is one pipeline: we pick the number nobody trusts, trace it back to its sources, and ship the automated flow that produces it — paid, scoped, and monitored from day one. You watch your own figures arrive on schedule before committing to anything larger, and if we carry on, we operate what we build. And if you'd rather co-own than commission — you bring the domain, we bring the build — see how we partner.
If your data moves by hand, by luck, or not at all, it should move on its own.
Tell us which numbers arrive late, who compiles them, and what breaks when they're wrong. We reply within two business days — hello@understandata.com.
Tell us about your numbers