{"apiVersion":"1","solution":{"slug":"managed-igaming-data-warehouse","title":"Managed iGaming data warehouses","summary":"Find a supplier-operated data foundation for casino and sportsbook analysis. Compare the work included in the service, the records your team can retrieve and the responsibilities that remain with your operation.","reviewedAt":"2026-10-10","canonicalUrl":"https://igamingdiscovery.com/solutions/managed-igaming-data-warehouse","jsonUrl":"https://igamingdiscovery.com/api/discovery/v1/solutions/managed-igaming-data-warehouse","operator":"AND","capabilityIds":["managed-data-warehouse"],"relatedTypes":["data-warehouses","business-intelligence","conversational-analytics"],"answer":"A managed iGaming data warehouse combines an analytical data store with a supplier's responsibility for operating it. It can be sold separately or explicitly included in a wider BI package; dashboards, cloud hosting or SQL access alone do not establish that service. Confirm the sources, maintenance duties and access terms for the actual product you are buying.","qualification":["The product has current evidence of a supplier-operated analytical warehouse, with hosting and operational responsibility described.","A wider platform qualifies when its own offer explicitly includes the managed warehouse; a related product from the same supplier is insufficient.","The evidence supports managed delivery for the named product. The proposal must still identify the sources, workload and continuing service covered."],"caveats":["Managed delivery does not automatically include unrestricted SQL, a data export API, every historical record or a particular retention period.","A warehouse does not automatically provide shared metric governance, AI investigations or predictive models. Check each additional capability and its package separately.","An absent product is not proof that the supplier cannot provide this service. This list requires current product-specific evidence, rather than a generic analytics claim."],"sections":[{"id":"warehouse-service-boundary","title":"Compare a running data service with a BI tool","paragraphs":["Start with the operating boundary. A BI interface helps people explore data; the warehouse service must also explain who runs the analytical environment behind it. Ask for a diagram separating source systems, ingestion, storage, transformations and the tools above them. Mark which components the supplier operates and which remain in your cloud or another provider's contract.","Deployment language needs care. DigerAnalytics describes deployment in the customer's infrastructure and connections for existing BI tools. Those statements establish a different boundary from an explicit managed-service inclusion; they do not resolve who performs every operating task. Conversely, Gamblitude's pricing expressly includes a managed warehouse with its BI subscription. Compare the named offer and responsibility schedule, rather than inferring delivery from the category label."],"sourceIds":["managed-diger-deployment","managed-gamblitude-package","managed-gamblitude-bi"]},{"id":"retained-team-responsibilities","title":"Assign the work that continues after onboarding","paragraphs":["Bring an inventory of source owners, access methods and known data gaps. Agree who maintains connectors, detects failed loads, handles schema changes and validates corrections. The supplier may operate the foundation while your team still approves source access, explains unusual transactions and decides whether a business definition is correct. Name the owner of each handoff, including a feed that stops outside the supplier's control.","Separate implementation from continuing service and future changes. Request scope for historical imports, new brands, extra sources, support, recovery and exit delivery. Compare equivalent workloads and retained internal effort. A managed subscription does not establish a launch date, response time or saving for your operation; those need a scoped proposal and appropriate acceptance evidence."],"sourceIds":["managed-gamblitude-responsibilities","managed-gamblitude-package","managed-gamblitude-warehouse"]},{"id":"history-access-and-meaning","title":"Keep usable history and verify its meaning","paragraphs":["Ask for the detail behind one monthly total: individual bets or rounds, payments, timestamps, identifiers and relevant status changes. Specify the available backfill, retention and correction behaviour. Event-level storage and customer access are separate questions. Demonstrate the proposed investigation and export route using a bounded sample, then confirm permissions and what can be retrieved when the service ends.","Storage alone also cannot settle a disagreement about NGR. Document deductions, eligible activity, currency, reporting period and late adjustments. If a metric layer is included, trace a named definition into the proposed BI or AI output. Keep legitimate finance and marketing variants explicit. Supplier material can describe shared definitions, but your team must validate their configured meaning against the source records."],"sourceIds":["managed-gamblitude-warehouse","managed-gamblitude-bi","managed-gamblitude-definitions","managed-diger-deployment"]}],"questions":[{"id":"managed-warehouse-operating-scope","question":"Which warehouse operating tasks does this contract include?","why":"Request a responsibility schedule covering infrastructure, ingestion, monitoring, failed loads and source changes; identify exclusions before comparing offers.","requirement":"Document warehouse hosting and operating duties, exclusions and named owners for failures and source changes.","sourceIds":["managed-gamblitude-responsibilities","managed-gamblitude-package"]},{"id":"managed-warehouse-history","question":"Which historical records will be retained and reconciled?","why":"Use a sample with a late event and correction to check backfill, identifiers and control totals, rather than accepting an aggregate chart as proof.","requirement":"Agree event granularity, backfill, retention, correction handling and reconciliation against representative source records.","sourceIds":["managed-gamblitude-warehouse"]},{"id":"managed-warehouse-access","question":"How can our team retrieve data during the service and at exit?","why":"Inspect supported interfaces, fields and permissions. Demonstrate the agreed export or query path; an ingestion API does not establish outbound access.","requirement":"Demonstrate agreed customer data access, fields, permissions and usable exit exports, with delivery terms.","sourceIds":["managed-gamblitude-bi","managed-diger-deployment"]},{"id":"managed-warehouse-definitions","question":"Is shared metric governance included, and who approves it?","why":"Trace one calculation through the proposed outputs and reconcile intentional variants. Warehouse operation and business-definition ownership are separate responsibilities.","requirement":"Identify included metric governance, approval owners and how each agreed definition is reused and validated across outputs.","sourceIds":["managed-gamblitude-definitions","managed-gamblitude-responsibilities"]},{"id":"managed-warehouse-change-cost","question":"What changes the service scope and commercial quote?","why":"Price the same sources, history, workload and support needs. Make onboarding, subsequent integrations, recovery commitments and transition assistance explicit.","requirement":"Itemise setup, ongoing service, change work and exit assistance for an agreed data scope and workload.","sourceIds":["managed-gamblitude-package","managed-gamblitude-responsibilities"]}],"sources":[{"id":"managed-gamblitude-warehouse","label":"Managed lakehouse, event history and ingestion scope","url":"https://gamblitude.ai/products/data-warehouse-for-igaming/","publisher":"Gamblitude","checkedAt":"2026-10-10","supports":"Current product material describes a managed cloud lakehouse, retained granular events and implementation-specific ingestion, backfill and freshness."},{"id":"managed-gamblitude-package","label":"Explicit warehouse inclusion and commercial boundaries","url":"https://gamblitude.ai/pricing/","publisher":"Gamblitude","checkedAt":"2026-10-10","supports":"The BI subscription explicitly includes a managed warehouse; setup and predictive models have separate scope. No published price is used as a quote for a buyer."},{"id":"managed-gamblitude-responsibilities","label":"Managed delivery and retained operator responsibilities","url":"https://gamblitude.ai/problems/high-in-house-costs/","publisher":"Gamblitude","checkedAt":"2026-10-10","supports":"Distinguishes infrastructure and continuing service from source access, business definitions, validation and operational decisions retained by the operator."},{"id":"managed-gamblitude-definitions","label":"Calculation meaning and source reconciliation","url":"https://gamblitude.ai/problems/conflicting-kpis/","publisher":"Gamblitude","checkedAt":"2026-10-10","supports":"Explains formula, population, time and source-coverage differences, with named metric variants and validation across analytical outputs."},{"id":"managed-gamblitude-bi","label":"BI access, shared definitions and agreed outputs","url":"https://gamblitude.ai/products/business-intelligence-platform-for-igaming/","publisher":"Gamblitude","checkedAt":"2026-10-10","supports":"Describes shared Metrics and Attributes, connected activity history, CSV exports and agreed API connections; no unrestricted SQL or export API is inferred."},{"id":"managed-diger-deployment","label":"Customer infrastructure, history and BI connections","url":"https://diger.io/analytics","publisher":"Diger","checkedAt":"2026-10-10","supports":"Describes deployment in customer infrastructure, granular historical records and JDBC/ODBC connections. These facts do not establish a supplier-operated warehouse service."}],"requirements":[{"id":"managed-data-warehouse","label":"Managed data warehouse","group":"Data foundation","definition":"The supplier operates a persistent analytical data warehouse for the customer. A dashboard, data feed or customer-managed database alone does not qualify.","aliases":["managed warehouse","managed DWH"],"requirement":"A supplier-operated analytical data warehouse, with hosting and operational responsibilities documented.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"]}]},"capabilityEvidenceMeaning":"Documented means supported by the cited supplier material, not independently tested. Unknown is not a negative finding. Conditional capabilities do not count as strict matches. Evidence applies to the named product only; it does not establish live integrations, contractual availability or measured outcomes.","capabilitySearch":{"vocabularyVersion":"2026-10-10.4","scope":"data-ai","operator":"AND","selected":["managed-data-warehouse"],"mode":"documented","eligibleProducts":33,"reviewedProducts":33,"documentedCount":2,"confirmationCount":31,"excludedCount":0,"facets":[{"id":"managed-data-warehouse","label":"Managed data warehouse","group":"Data foundation","definition":"The supplier operates a persistent analytical data warehouse for the customer. A dashboard, data feed or customer-managed database alone does not qualify.","aliases":["managed warehouse","managed DWH"],"requirement":"A supplier-operated analytical data warehouse, with hosting and operational responsibilities documented.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":2,"confirmationCount":31},{"id":"event-level-history","label":"Historical event-level data","group":"Data foundation","definition":"Retained individual historical events or transactions can be analysed. Aggregated historical charts alone do not qualify; retention duration must be confirmed separately.","aliases":["transaction-level history","granular event history"],"requirement":"Analysis of retained event-level or transaction-level history, with retention and available fields confirmed.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":2,"confirmationCount":31},{"id":"shared-metric-definitions","label":"Shared metric definitions","group":"Business metrics","definition":"A reusable governed metric or semantic layer supplies consistent definitions across analytical outputs. Merely listing KPI dashboards does not qualify.","aliases":["semantic layer","governed metrics","metric system"],"requirement":"Shared, governed metric definitions reused across reports and analytical outputs.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":2,"confirmationCount":31},{"id":"custom-metrics","label":"Custom business metrics","group":"Business metrics","definition":"The product supports defining business-specific calculated metrics or formulas. Customising a dashboard layout alone does not qualify.","aliases":["calculated metrics","custom KPIs"],"requirement":"The ability to define business-specific calculated metrics or formulas.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":1,"confirmationCount":32},{"id":"natural-language-analytics","label":"Natural-language analytics","group":"AI analysis","definition":"Users ask analytical questions in natural language and receive answers grounded in data available to this product. A general support chatbot does not qualify.","aliases":["conversational analytics","ask your data","AI analyst"],"requirement":"Natural-language analytical questions answered using the data available to the product.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":1,"confirmationCount":32},{"id":"multi-step-investigations","label":"Multi-step investigations","group":"AI analysis","definition":"The product carries out a sequence of analytical steps to investigate a question, for example forming hypotheses and drilling into contributing factors. Single-query answers alone do not qualify.","aliases":["root cause investigation","multi-step analysis"],"requirement":"Multi-step analytical investigations with intermediate findings and contributing factors.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":0,"confirmationCount":33},{"id":"autonomous-investigations","label":"Autonomous investigations","group":"Autonomy","definition":"The product selects analytical topics or investigative paths and initiates investigations without a separate user question or predefined recurring check. Monitoring, events or a standing goal may provide context, but chat-driven analysis, a user-defined scheduled investigation, a threshold alert or a scheduled report alone does not qualify. This does not imply execution of external business actions.","aliases":["autonomous analyst","autonomous agent"],"requirement":"System-initiated analytical investigations with topic or path selection, beyond user-defined recurring checks, with initiation and scope documented.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":1,"confirmationCount":32},{"id":"proactive-monitoring","label":"Proactive monitoring","group":"Autonomy","definition":"The product monitors data and surfaces detected changes, risks or anomalies without an ad hoc analytical query. A static dashboard or scheduled report alone does not qualify.","aliases":["anomaly monitoring","proactive alerts"],"requirement":"Monitoring that surfaces detected changes, risks or anomalies without an ad hoc query.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":1,"confirmationCount":32},{"id":"scheduled-ai-investigations","label":"Scheduled AI investigations","group":"AI analysis","definition":"Users define an analytical question or investigation and schedule AI to repeat the analysis and return findings with context. A threshold alert, continuous risk score, dashboard subscription or recurring report alone does not qualify. This is distinct from an agent choosing its own investigative topics.","aliases":["recurring AI investigations","scheduled analytical checks"],"requirement":"User-defined analytical investigations repeated by AI on an agreed schedule, with findings and context returned for review.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":1,"confirmationCount":32},{"id":"mcp-analytics-access","label":"Analytics access through MCP","group":"Data access","definition":"Customer-enabled external AI tools can use a documented Model Context Protocol connection to read analytical data, metrics, dashboards, reports or insights from the named product. An ordinary API, developer SDK or internal use of MCP alone does not qualify. Supported objects, permissions and setup require confirmation; this does not establish write access or business-action execution.","aliases":["MCP analytics server","Model Context Protocol analytics"],"requirement":"A documented MCP connection for external AI tools to read the product’s analytical data or outputs, with scope and permissions confirmed.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":1,"confirmationCount":32},{"id":"ai-generated-reports","label":"AI-generated analytical reports","group":"AI analysis","definition":"The product generates an analytical report from a user brief or request, combining data-grounded written analysis with charts or other data visualisations in a report document. Static exports, templates, scheduled dashboard snapshots or isolated chat answers alone do not qualify. Scheduling, export formats and delivery channels require separate confirmation.","aliases":["AI-written reports","generative analytics reports"],"requirement":"Analytical reports generated from a brief, combining supporting data visualisations and written analysis for human review.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":1,"confirmationCount":32},{"id":"data-export-api","label":"Data export API","group":"Data access","definition":"A documented API lets the customer retrieve analytical data, reports or results from this product. An ingestion-only API, partner logo or unrelated supplier API does not qualify.","aliases":["reporting API","analytics export API"],"requirement":"API retrieval of analytical data, reports or results, with available fields and access conditions confirmed.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":0,"confirmationCount":33},{"id":"direct-sql-access","label":"Direct SQL access","group":"Data access","definition":"Customer users or tools can query product data using SQL through a documented query surface or database connection. SQL used only internally by the supplier does not qualify.","aliases":["SQL querying","SQL connection"],"requirement":"Customer-accessible SQL querying of analytical data, with permissions and access method documented.","scope":"data-ai","productTypeSlugs":["business-intelligence","data-warehouses","conversational-analytics","player-analytics","predictive-analytics"],"documentedCount":0,"confirmationCount":33}],"relaxations":[]},"items":[{"id":"11","slug":"gamblitude-business-intelligence","name":"Business Intelligence Platform","supplierSlug":"gamblitude","supplierName":"Gamblitude","canonicalUrl":"https://igamingdiscovery.com/products/gamblitude-business-intelligence","productTypeSlugs":["business-intelligence","player-analytics"],"summary":"Self-service dashboards, Segments, Reports and Targets for iGaming teams.","capabilityReview":{"vocabularyVersion":"2026-10-10.4","scope":"product","reviewState":"reviewed","reviewedAt":"2026-10-10","reviewDueAt":"2027-04-08"},"capabilityMatch":{"status":"documented","operator":"AND","requested":["managed-data-warehouse"],"documented":["managed-data-warehouse"],"conditional":[],"unknown":[],"notSupported":[],"notApplicable":[],"requirements":[{"capabilityId":"managed-data-warehouse","label":"Managed data warehouse","status":"documented","summary":"The BI subscription includes a dedicated cloud warehouse operated by Gamblitude for the agreed data sources.","conditions":null,"sources":[{"id":"gamblitude-bi-pricing","url":"https://gamblitude.ai/pricing/","title":"Gamblitude Pricing | iGaming BI & AI from €3,000/month","publisher":"Gamblitude","checkedAt":"2026-10-10","supports":"The standard subscription expressly includes a supplier-managed warehouse, the BI platform, AI Agent, Insight Radar and Autonomous Agent."}]}]},"links":{"profile":"https://igamingdiscovery.com/products/gamblitude-business-intelligence","evidence":"https://igamingdiscovery.com/api/discovery/v1/products/gamblitude-business-intelligence"}},{"id":"10","slug":"gamblitude-data-warehouse","name":"Data Warehouse","supplierSlug":"gamblitude","supplierName":"Gamblitude","canonicalUrl":"https://igamingdiscovery.com/products/gamblitude-data-warehouse","productTypeSlugs":["data-warehouses"],"summary":"Managed data infrastructure for operational iGaming events and shared metrics.","capabilityReview":{"vocabularyVersion":"2026-10-10.4","scope":"product","reviewState":"reviewed","reviewedAt":"2026-10-10","reviewDueAt":"2027-04-08"},"capabilityMatch":{"status":"documented","operator":"AND","requested":["managed-data-warehouse"],"documented":["managed-data-warehouse"],"conditional":[],"unknown":[],"notSupported":[],"notApplicable":[],"requirements":[{"capabilityId":"managed-data-warehouse","label":"Managed data warehouse","status":"documented","summary":"Gamblitude supplies a managed cloud lakehouse for connected iGaming operational data.","conditions":null,"sources":[{"id":"gamblitude-warehouse-product","url":"https://gamblitude.ai/products/data-warehouse-for-igaming/","title":"iGaming Data Warehouse for Analytics & AI | Gamblitude","publisher":"Gamblitude","checkedAt":"2026-10-10","supports":"Managed cloud lakehouse; retained granular bets, sessions, payments and other operational events; shared KPI definitions applied through a governed metric layer."}]}]},"links":{"profile":"https://igamingdiscovery.com/products/gamblitude-data-warehouse","evidence":"https://igamingdiscovery.com/api/discovery/v1/products/gamblitude-data-warehouse"}}],"pagination":{"page":1,"pageSize":24,"total":2,"totalPages":1,"next":null,"previous":null}}