N-and operates at the intersection of physical and digital commerce: thousands of vending machines in the field, a consumer loyalty app, and a growing need to turn fragmented operational data into business value. By adopting Mia-Platform Fast Data, we unified two fundamentally different data worlds: telemetry streams from machines on field — carrying purchase transactions, audit trails, and operational signals — and behavioral events from the CoffeeApp, including loyalty interactions, ad engagement, and redemptions. The result is a set of Data Products that give the entire organization a single, trusted view of customers, machines, and transactions. What makes this journey distinctive is how we accelerated delivery. We developed AI-powered skills that automate the creation of Single View configurations directly from incoming event schemas and aggregation templates, dramatically reducing the time from data source to Data Product. Alongside this, we adopted decision tables — driven by business rules written in Rego — to express complex aggregation logic in a format that business and technology teams can read, validate, and evolve together, without touching the underlying pipeline code. The outcome is a scalable, event-driven infrastructure where real-time data from the physical and digital world converges into standardized views that feed dashboards, operational systems, and AI agents — and where the rules that govern that data are owned by the business, not buried in code.
LANGUAGE
English
LEVEL
Intermediate
FORMAT
Talk
