A dashboard is not a data strategy. This comparison separates the reporting surface, real-time views, standard metrics, dashboard control, analytical exports, warehouse access, and cohort analysis across all 18 providers.
Last updated August 20, 2026 · 18 providers · overall-score order, not a BI score
18/18
BI conclusions marked Yes
16/18
real-time reporting conclusions marked Yes
15/18
dashboard conclusions marked Yes
13/18
analytics-export conclusions marked Yes
14/18
warehouse conclusions marked Yes
15/18
cohort / funnel conclusions marked Yes
These cards count the primary field value. A Yes can still be limited to one product, an API or export route, or a partial workflow; the boundary shown with every provider controls the conclusion.
Each capability answers a different operator question. A Yes in one column does not fill another.
A named reporting product fixes the conclusion to that surface. Provider-level conclusions are not extended across every module in the portfolio.
The field establishes a real-time reporting mode. It does not establish seconds, refresh cadence, correction behavior, or service availability.
A customizable screen can exist without raw export or warehouse delivery. A warehouse feed can exist without a strong self-service dashboard.
The analytics-export field covers reporting use. Contractual ownership, complete history, replacement-provider handoff, and exit cost are separate rights.
Product names appear only where that product's reporting capability is established. Unresolved remains unresolved; it is never converted to No. Provider order follows the site-wide holistic score.
Rank 01
Product-level scope
DataHub streams into a dedicated Kafka cluster for client BI/DWH consumption.
Rank 02
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
Financial reporting plus player lifecycle and segmentation metrics are standard IMS outputs.
Operational reporting and integrations are supported. Full player, wallet, compliance, CRM, bonus and audit-history portability is contract-specific.
Real-time event feeds, APIs, exports and Power BI/partner analytics integrations support operator data platforms; the exact connector set is deployment-specific.
Rank 03
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
Sportsbook reporting segments live versus pre-match turnover, margin, average stake, device, fixture and player-product crossover. Metric-accuracy validation remains unresolved.
Report Builder centers on GGR across casinos, providers, games and timeframes. The KPI framework also covers NGR, active players and LTV.
Reports are built from a customizable framework with up to four levels of data grouping rather than free-form drag-and-drop widgets.
Back office exports plus Event Streaming, which can feed real-time event data to external services for analytics.
Partial. Event Streaming can feed an operator's external analytics stack and affiliated Bambi Data offers data tooling; native Snowflake and BigQuery connectors are not established.
Cohort and segment analysis is supported through real-time player segmentation and Report Builder. A dedicated funnel view remains unresolved.
Rank 04
Product-level scope
Data Lake gives real-time access to core platform data plus a built-in BI suite called Insights, and operators can plug in third-party or in-house analytics instead.
Data Lake exposes core platform datasets in real time for reporting and analysis.
Real-time analysis via the Data Lake and the 'Insights' BI suite.
Data Lake exposes fully documented table views (with data dictionary and lineage) and retains full historical data; operators can pipe it to their own analytics.
Operators can use the out-of-the-box 'Insights' suite, plug in a third-party BI platform, or use their own in-house analytics/warehouse against the Data Lake.
The available real-time and historical data supports cohort and funnel work; exact built-in Insights views remain unresolved.
Rank 05
Product-level scope
Michigan provides customer-specified extraction; NeoCube exposes raw iLottery data. Other modules remain contract-specific.
NeoCube is an omnichannel iLottery data warehouse and BI lake; this does not establish a universal warehouse connector for every module.
Analytics products exist, but the cross-product cohort and funnel feature specification remains unresolved.
Rank 06
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
Reporting is established, but operator-built custom dashboards are not.
Auditor-ready regulatory exports, open APIs, BI dashboards and configurable reporting are available. Complete player-level bulk export, formats, schemas, history depth and portability rights remain unresolved.
Fast Track and Optimove integrations do not establish an operator warehouse integration.
Detailed player analytics and open APIs let operators map user journeys and test conversion models, supported by BI dashboards and configurable reports. A dedicated cohort-builder specification remains unresolved.
Rank 07
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
Customer intelligence and reporting built on network data and an OpenText data warehouse.
Real-time betting data across the network; operator-facing dashboards per deployment.
Data feeds and warehouse access are available to partners; exact formats are partner-gated.
OpenText data warehouse ingests production and third-party data; real-time data can be pushed to the operator's environment.
Customer intelligence, real-time reporting and player-journey analytics support cohort and conversion analysis, although dashboard details are partner-gated.
Rank 08
Product-level scope
Yes through OPS/partner portal.
Yes — APIs, portal exports and reporting.
Yes through APIs and data integrations.
Supported through OPS data and operator BI.
Rank 09
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
Yes for content, game and campaign operations.
Partial — real-time tournament leaderboards and operational/game feeds; full operator BI remains outside scope.
Partial — Fusion back-office views and campaign reporting, not a general-purpose operator BI builder.
Partial — campaign/leaderboard and service views.
Partial — API and portal/report downloads; exact financial export formats are partner-gated.
Possible through operator APIs and data flows; a packaged warehouse connector catalogue is not established.
No full player-funnel analytics.
Rank 10
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
LTV and lifecycle metrics are available in CRM context; a unified metric dictionary remains unresolved.
APIs, feed archives and configurable reporting expose data, but complete bulk-file formats, database portability and warehouse delivery remain contract-specific.
Snowflake, BigQuery, Redshift, Databricks and operator-owned warehouse connectors remain unresolved.
Centrivo CRM's lifecycle segmentation, player journeys, conversion dashboards and comparative campaign analysis provide practical cohort and funnel analysis; the formal methodology remains unresolved.
Rank 11
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
The single back office includes administration and reporting across brands and states.
State ledgers, risk alerts and complete player history are available in real time.
These are the core PAM, cashier and regulatory-reporting measures; the exact standard metric set remains unresolved.
Partial. Standard reporting is present; self-serve dashboard building is not established.
Real-time risk, player and ledger data are established; the complete live-dashboard set remains unresolved.
White Hat provides Kafka/Segment events, downloadable management reporting and no-charge export of all Customer Information at exit for operator-licensed PAM.
The architecture includes a Data Warehouse, and Kafka/Segment can feed downstream systems. Named Snowflake or BigQuery connectors remain unresolved.
Partial. Integrated CRM tools perform journey and segment analysis; a separate native cohort module is not established.
Rank 12
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
APIs, real-time streams and bulk exports support an operator warehouse; a turnkey connector inventory remains unresolved.
Rank 13
Product-level scope
DataX is platform-agnostic and supports SQL connectivity and external data delivery; dedicated Snowflake, BigQuery or Redshift connectors are not established.
Rank 14
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
Yes — shared data platform and operator reporting.
Configurable operator dashboards; exact self-service depth is private.
Real-time operational and player views are available; exact dashboard scope remains unresolved.
Yes for reporting, audit and operator analysis.
Possible through APIs and exports; named warehouse connectors remain unresolved.
Supported by journey and behavioural analytics; the exact interface remains unresolved.
Rank 15
Product-level scope
Player and project dashboards are current; deeper reports remain period-filtered.
Reporting also covers unique players, average bet, withdrawals, first deposit, profitability and CPR. NGR and LTV were not established as named out-of-the-box metrics.
The BI module exposes standard metrics and filters but not a fully custom dashboard builder.
BI reports export to CSV and XLS.
An internal analytics/data layer exists; an external customer warehouse connector is not established.
A native cohort or conversion-funnel analysis workflow is not established.
Rank 16
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
Operators can build custom reports and set them for automated delivery, and pull data through the platform's external APIs.
A Tableau Data Warehouse component is actively released and monitored; CRM segmentation also supports BigQuery data ingestion.
Rank 17
Product-level scope
Product-specific scope unresolved. Values remain provider-level.
A centralized dashboard pulls data from integrated providers and the analytics engine pushes real-time data updates.
Report export and automated report generation are available; a separate BI data feed or API remains unresolved.
A native warehouse connector is not established.
Partial through standard player and campaign reports.
Rank 18
Product-level scope
Dashboards also cover ARPU, retention, deposits, payment approval, sportsbook handle, and hold.
The warehouse stack is Snowflake on AWS with S3 and RDS.
BI reporting is the broader capability to analyze operational, player, financial, product, risk, and marketing data. A real-time dashboard is one interface within that capability. It can expose current operational views without providing historical modeling, warehouse access, custom metrics, or a complete export.
No. Real-time is a capability classification, not a measured delivery-time promise. Procurement must define source timestamps, refresh cadence, batch windows, correction behavior, availability, and acceptance tests for each required dataset.
No. An analytics export can be filtered, aggregated, delayed, or limited to a reporting schema. Exit portability requires the contractual right to receive the complete agreed history, stable identifiers, balances, compliance state, configurations, and transition support in a usable replacement-platform format.
At minimum, define GGR, NGR, turnover, margin, active player, FTD, retention, LTV, bonus cost, deposits, withdrawals, payment approval, and risk measures used in the business case. Each definition needs currency, timezone, event state, void and rollback treatment, tax and bonus treatment, and reconciliation ownership.
A provider can offer reporting for one platform, sportsbook, PAM, lottery stack, affiliate product, or engagement module without establishing identical coverage across the rest of its portfolio. Product names appear only where that product's capability is established; all other values remain provider-level conclusions with their stated boundaries.