Engagements, in the shape they usually take.
Illustrative descriptions of the technical problems Novriq Labs solves across multi-platform data stacks.
Illustrative engagements. These describe the kind of work Novriq Labs does, not delivered client projects, and they carry no client names, figures, or results. Replace them as real case studies become available.
E-commerce analytics pipeline
Data was fragmented across multiple commerce and advertising platforms, each with its own definition of a sale.
A centralized pipeline connecting Shopify, GA4 and the advertising APIs, with normalization and validation before anything reached the warehouse.
A unified analytics layer powering business dashboards from a single set of models.
Paid media reporting layer
Spend and performance lived in three ad platforms with different attribution windows and reporting lags.
Incremental extraction per platform with restatement handling, then a conformed model that expresses spend, delivery and conversion on one calendar.
One reporting layer that can be compared across channels without manual reconciliation.
CRM and revenue reconciliation
The CRM and the commerce platform disagreed on which customers and orders existed.
Identity resolution across systems, a reconciliation model that records disagreements rather than hiding them, and checks that surface breaks as they appear.
A revenue view whose differences are explainable instead of unexplained.