Your Data Testing ROI Calculated in 2 Minutes

The figures are indicative estimates — derived from average outcomes across 100+ Datagaps enterprise deployments. They give a credible directional view of the magnitude of savings available, but are not a contractual projection. Actual results depend on environment scale, existing tooling, team structure, and how broadly Datagaps is deployed. Adjusting the assumptions in each calculator tab to reflect your own numbers will bring the output closer to your environment.

Based on 100+ enterprise deployments, the investment is typically recovered within 3 to 6 months. The primary driver is the elimination of manual testing labour — which in most data teams represents a recurring, high-volume cost across ETL, BI, and compliance workstreams. After payback, the savings compound with every subsequent test cycle.

The model compares your current manual cost — inputs multiplied by standard manual testing time per test case and an engineer hourly rate — against the automated cost, which reflects reduced execution time plus the Datagaps licence. All default assumptions (hourly rate, minutes per test case, automated execution time, annual licence cost) are fully visible and editable in the Adjust Assumptions section of each calculator tab. We recommend reviewing and updating these before drawing conclusions.

The ROI multiple is the ratio of total savings generated to the total cost of the platform. A 7× return means that for every $1 spent on Datagaps — licence, implementation, and ongoing cost — the organisation recovers $7 in testing labour savings. The multiple is independent of scale, which makes it useful for comparing the efficiency of the investment across different environment sizes.

Yes, with appropriate framing. These are indicative estimates based on industry benchmarks — they give a credible starting point for an investment evaluation, not a guaranteed outcome. The case studies on this page provide documented, real-world evidence to support the figures. For a more precise analysis built on your specific data volumes and team structure, a free ROI Validation Workshop with our team is the most efficient next step.

Yes. Datagaps offers a structured free trial and a proof-of-value programme. We also run a free 30-minute ROI Validation Workshop — a working session where our team maps your environment against deployment benchmarks and produces a tailored financial model. There is no commercial obligation attached.
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The comparison is best understood at the total cost of ownership level, not product-by-product.

Datagaps vs. iceDQ · QuerySurge · Wiiisdom

• Platform breadth reduces total spend: iceDQ and QuerySurge address ETL testing only. Wiiisdom addresses BI analytics only. Datagaps covers ETL, BI validation, data quality monitoring, compliance reporting, and test data management in a single platform — eliminating the need for multiple point-tool licences and the integration overhead between them.
• AI automation reduces ongoing labour: Datagaps uses Agentic AI to generate test cases and adapt to schema changes automatically. iceDQ and QuerySurge require ongoing manual test maintenance. Customers moving from QuerySurge to Datagaps report a further 25–40% reduction in ongoing testing labour from AI-driven automation alone.
• Independent recognition: Datagaps is the only vendor listed in both the Gartner® DataOps Tools and Data Observability Market Guides. No comparable listing exists for iceDQ, QuerySurge, or Wiiisdom.

Yes, with documented deployments in all three. In Financial Services: SOX-compliant financial reporting, NAIC MAR reconciliation automation, and mainframe-to-cloud migration validation. In Healthcare: APCD submission automation, HIPAA-compliant pipeline validation, and clinical data testing. In Life Sciences: 21 CFR Part 11 compliant validation workflows. In regulated environments, the cost of a data error — through audit findings, rework, or compliance penalties — typically makes the financial case for automation significantly stronger than the calculator alone captures. 
See industry-specific deployments →

Pricing is scoped to your environment — number of data sources, test case volume, and which Datagaps products you deploy. Most enterprise customers recover the annual licence cost within the first quarter of operation from labour savings alone. A scoped commercial proposal is typically available within a few business days of an initial conversation. 
View pricing overview →

Datagaps connects to 200+ data sources — including Snowflake, Databricks, Azure Synapse, Salesforce, SAP, and Oracle. BI Validator integrates natively with Power BI, Tableau, and Oracle Analytics. Your existing infrastructure stays in place — Datagaps validates it without requiring changes to the underlying stack or re-architecting pipelines.