Published March 2026 · Smartlinks Case Study
A Series A fintech startup came to Smartlinks with a familiar problem — their data was everywhere and nowhere at the same time. Transactions lived in their payments database, customer behaviour in a third-party analytics tool, support tickets in Zendesk, and marketing data in HubSpot. Getting a single view of a customer required a data analyst to spend half a day pulling reports manually.
As the company scaled from 10,000 to 80,000 users in eight months, the manual reporting process completely broke down. Leadership was making decisions on week-old data. The data team was drowning in ad hoc requests.
We began with a two-week discovery process, mapping every data source, understanding the business questions that needed answering, and designing a target architecture. The solution centred on a modern data stack: Fivetran for automated data ingestion, Snowflake as the central data warehouse, dbt for data transformation, and Metabase for self-service analytics.
Within six weeks, the entire pipeline was live. Every data source was streaming into Snowflake automatically. The data team had a clean, documented set of dbt models. And every team in the company had access to a self-service dashboard with real-time data.
The impact was immediate and measurable. Reporting time dropped from half a day to under five minutes — an 80% reduction. The data team went from spending 70% of their time on ad hoc requests to focusing entirely on strategic analysis. Leadership now reviews live dashboards in their weekly meetings instead of waiting for manual reports.
The biggest lesson from this engagement was that the technology was the easy part. The hard work was change management — getting every team to trust the new data and update their workflows.
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