iGaming Data Engineering, Analytics & Reporting

Yes, when the necessary records and identifiers are available. We map timing, currency and calculation differences, identify unmatched items and distinguish true discrepancies from expected settlement or reporting delays.

The required freshness is agreed for each decision and source. Some data can be streamed, while other records arrive in batches or require finalization. We display and monitor the actual freshness rather than applying a universal real-time label.

Yes. We can build or improve the underlying data model and pipelines, then connect the organization’s chosen BI tools where appropriate. Tool replacement is not assumed to be necessary.

We document definitions and source ownership, centralize agreed calculations where practical and test representative reports against source data. Revisions and exclusions are recorded so teams can explain why totals differ.

We can scope funnels and cohorts around agreed account and event identifiers, with definitions for registration, a qualifying first deposit, a game session and a returning player. Reports distinguish event time from processing time and expose missing or delayed data. Product and marketing teams can then investigate where journeys change; a dashboard alone does not prove that a campaign caused a revenue or retention change.

We start with representative questions, source volumes, freshness targets, retention and access patterns. Candidate storage and query designs are compared using a stated workload, including dashboard concurrency, drilldowns, backfills and exports. Acceptance records query response times, data freshness and infrastructure costs in the tested environment. We can retain an existing warehouse where it meets those needs; a database name or a successful demo alone does not establish production performance or operating cost.

The metric owner agrees the financial definition, event or posting dates, cutoff, time zone, currency and correction policy. A report can show an operational estimate while transactions remain open; a closed period needs controlled adjustment or restatement behavior. We preserve the source references and model version, then reconcile revised totals against the authoritative records. GGR, NGR, bonus cost and affiliate revenue definitions are not assumed to be interchangeable.

They can use governed datasets and role-specific views when the selected architecture supports them. We scope brand and row boundaries, sensitive columns, aggregation, retention and query or export permissions around each task. A support investigation may need controlled references that a marketing dashboard should not receive. Acceptance tests permitted and denied access, scheduled downloads and audit evidence; adding a dashboard login alone does not establish those boundaries.

The scope identifies source access, ingestion jobs, transformation code, tested models, metric definitions, lineage, quality rules and the chosen dashboards or BI connections. The acceptance pack reconciles known records and totals and exercises schema changes, delayed data, backfills and recovery against agreed freshness and performance targets. We document environments, credentials, infrastructure and operating costs, support ownership and available exports. A third-party data licence or an ongoing analytics team is a separate dependency.