DataRadar™ Puts Every Snowflake Credit Behind Data You Can Trust
DataRadar™ makes Snowflake® data AI-ready. It is the only Snowflake Native App that unifies data quality monitoring and cost optimization, so every Snowflake credit funds reliable, healthy, performant, and understood data before it reaches AI.
AI Does Not Fail on Models. It Fails on Data That Was Never Ready.
Why do most AI projects on Snowflake® stall before production?
Most AI initiatives never reach production, and the cause is rarely the model or the talent. It is the data underneath: stale pipelines, silent schema changes, duplicate records, and inputs nobody can vouch for. AI amplifies every one of those flaws. Gartner predicts organizations will abandon 60% of AI projects not supported by AI-ready data, and 63% of organizations either lack or are unsure they have the right data management practices for AI (Gartner, 2025).
The tools meant to catch this fall into two camps. Quality tools watch pipelines but cannot see what unready data costs. Cost tools watch spend but cannot see why it is wasted. Neither can tell you whether the data you are paying for is ready for AI.
The AI-readiness gap, why observability split in two, and the path to one platform are covered in the Enterprise Playbook for Data Observability.
The DataRadar Observability Framework: What AI-Ready Data Looks Like
What makes Snowflake® data AI-ready?
AI-ready data clears four tests. The DataRadar Observability Framework measures every Snowflake workload against those four pillars, and the fifth pillar shows which Snowflake credits fund AI-ready data and which do not.
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DATA RELIABILITY
Accuracy, completeness, and consistency. Machine learning models learn your normal patterns and alert on anomalies, distribution shifts, and freshness delays with no manual thresholds.
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PIPELINE HEALTH
Lineage, volume, freshness, and schema change detection, so you know where data came from and why it broke before a model trains on it.
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PERFORMANCE OPTIMIZATION
Warehouse performance, query efficiency, and resource use, catching the bottlenecks that delay model training and inference.
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USAGE INTELLIGENCE
Utilization by user, role, and department, so you know which data the business depends on and where compliance exposure sits.
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COST VISIBILITY
Query-level cost attribution, warehouse right-sizing, budget alerts, and forecasting. Link every quality issue to the compute it consumes, so you can see which spend funds AI-ready data.
When a workload clears the first four pillars, the data is reliable, the pipelines are healthy, the queries are efficient, and you understand usage. That is AI-ready data. The savings come from stopping payments for data that never would have reached that point.
Built on Snowflake®. DataRadar™ Runs in Your Account. Your Data Never Leaves.
DataRadar on Snowflake at a Glance
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Category
AI-readiness platform for Snowflake: data observability with built-in cost optimization
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Partner Status
Powered by Snowflake Native App and a Snowflake partner since 2023
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Deployment
Snowflake Native App, installed from Snowflake Marketplace into your own account in under 30 minutes
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Data Egress
None. Zero-egress monitoring; data and metadata stay inside your Snowflake account
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Purchasing
Existing Snowflake credits through Marketplace Capacity Drawdown; counts toward committed use
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Trial
30-day free trial, self-service from Snowflake Marketplace
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Framework
Five pillars: data reliability, pipeline health, performance optimization, usage intelligence, cost visibility
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Alerts
Routed to Jira, Microsoft Teams, and xMatters
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Built For
CIOs, CDAOs, CFOs, data engineers, AI engineers, data governance, and analysts running Snowflake as a core platform
How a Fortune 500 Gaming Leader Got Its Snowflake Data AI-Ready
What does AI-ready data look like at Fortune 500 scale?
Caesars Entertainment runs DataRadar across more than five Snowflake environments and 30+ warehouses. Quality checks now run on critical datasets before they reach the business. The pipeline catches schema changes and anomalies, not a broken dashboard. Security has an audit trail that keeps them exam-ready. And the credits that were funding unready data? What Caesars put them toward is in the case study.
Frequently Asked Questions
What is DataRadar™?
DataRadar is a Snowflake Native App that makes Snowflake® data AI-ready. It unifies data quality monitoring and cost optimization in one application, runs inside your Snowflake account, and measures every workload against the five pillars of The DataRadar Observability Framework. DataRadar is a product of Confie.
What is AI-ready data?
AI-ready data is reliable, flows through healthy pipelines, performs at scale, and is understood by the business. Those are the first four pillars of The DataRadar Observability Framework. DataRadar tests every Snowflake workload against them, then uses cost visibility to show which spend funds AI-ready data and which doesn’t.
What is a Snowflake Native App?
A Snowflake Native App is an application installed from Snowflake Marketplace that runs entirely inside the customer’s own Snowflake account, using the customer’s compute and security controls. Data is never extracted to an outside system. A SaaS tool with a Snowflake connector is not a Native App.
Does DataRadar move my data outside Snowflake?
No. DataRadar™ uses zero-egress monitoring. Data and metadata stay inside your Snowflake account, and the app inherits your role-based access control, network policies, encryption, and audit logging. The only outbound traffic is alert notifications to Jira, Microsoft Teams, or xMatters.
Does DataRadar also reduce Snowflake costs?
Yes, as a result of AI-readiness. The failed pipelines, duplicate data, and inefficient queries that keep data from being AI-ready are the same problems that waste Snowflake credits. DataRadar links each one to the compute it consumes, so the spend you recover goes back into AI workloads that reach production.
How is DataRadar different from other Snowflake data observability tools?
Most quality tools cannot see what unready data costs, and most cost tools cannot see why spend is wasted. DataRadar is the only Snowflake Native App that does both in one application, so it can tell you whether the data you are paying for is ready for AI. One tool, one security review, one vendor.
How long does it take to install DataRadar from Snowflake Marketplace?
Under 30 minutes. Customers install DataRadar themselves from Snowflake Marketplace with no implementation project, no proof of concept, and no external infrastructure. Most teams see their first insights the same day.
Can I pay for DataRadar with Snowflake credits?
Yes. DataRadar participates in the Snowflake Marketplace Capacity Drawdown program, so purchases use existing Snowflake credits and count toward your committed-use requirements. There is no new vendor onboarding, no new budget line, and no procurement delay.
Is there a free trial of DataRadar?
Yes. DataRadar offers a 30-day free trial that you start yourself from Snowflake Marketplace. The trial runs in your own Snowflake account on your own data, so what you see during the trial is what you get in production.
Who is DataRadar built for?
DataRadar is built for enterprises running Snowflake as a core data platform, especially in financial services, insurance, healthcare, life sciences, travel, hospitality, and gaming. Users include CIOs, CDAOs, CFOs, data engineers, AI engineers, data governance teams, and analysts.
Trust Your Data. Control Your Costs. Power Your AI.
Start with the framework that defines AI-ready data on Snowflake, then see it running on your own data, in your own account, in under 30 minutes. Either way, your data never leaves.
$12.9M
avg. annual cost of poor data¹
70%
will adopt by 2027²
Only 40%
of AI prototypes succeed¹