Data Cleansing: the lucrative wheel with many hubcaps
There are lots of companies built on data-cleansing applications. It's the same formula:
- Ingestion: whatever the client throws at it.
- Validation: the domain standards — and every bespoke rule any client has ever dreamt up (if this, then that, but only on a Sunday with a blue moon and Venus rising). The more bespoke, the better the revenue stream.
- Cleansing: making it fit for the warehouse.
- Storing: putting it in the warehouse.
- Reporting: shipping it to Snowflake so a CEO can gaze at a dashboard and feel informed. Another revenue stream.
Most SMEs are ploughing the "file source" furrow: CSVs, spreadsheets, JSONs, XML, 3 a.m. SFTP drops — that sort of thing. A few of them, while growing, get themselves tangled in Kafka (a truly ironically named piece of software). That simple Kafka-Snowflake link, anyone? The Trial, indeed — endless steps, no clear reason, and somehow it’s always your fault.
So what's the special sauce? What allows for so many hubcaps on basically the same wheel? Bespokery, domain knowledge, super-specificity, and a willingness to really meet the client where they're at — often to the point where the SME feels like an unofficial department of the larger company. Bending over backwards, embracing the asymmetrical dance, where the question "Do we ever say 'No?'" is met with blank uncomprehending stares.
Insurance, fintech sub-niches galore, health, law, hospitality, energy — each gets its own branded hubcap, and another SME is born with a "founder" story and a come-hither look at Private Equity across the corporate dance-floor.