The Data Paradox
Most growing businesses are sitting on enormous amounts of data — CRM records, transaction logs, user behaviour data, support tickets — and yet very few are extracting real value from it. The data is there, but it's messy, siloed, and often unstructured.
Start with the Right Questions
The biggest mistake companies make is collecting data before defining the questions they want to answer. Before building any analytics pipeline, ask: What decisions do I need to make? What would change if I had this information? What does good look like? Working backwards from desired insight to required data is far more effective than the inverse.
Building a Data Pipeline That Scales
A modern data stack — typically combining a cloud data warehouse (BigQuery, Snowflake), a transformation layer (dbt), and a BI tool (Metabase, Looker) — can be set up in weeks, not months. The key is starting with your most critical use case and expanding from there.
Turning Data into Decisions
Data only has value when it changes behaviour. The best data teams create dashboards that are actually used in daily standups, weekly reviews, and key decision moments. At Spilneo, we help clients build data infrastructure that becomes a core part of their operating rhythm — not just a reporting afterthought.
