Startup Monte Carlo Data Inc. today debuted a new tool, the Data Product Dashboard, that can help companies spot quality issues in their business information.

San Francisco-based Monte Carlo is backed by more than $230 million in funding. It provides a data observability platform that helps companies ensure the information they use to make business decisions is accurate. The startup’s platform can spot duplicate records, out-of-date details and other data quality problems.

Its new Data Product Dashboard promises to further ease the task of spotting issues in business information and also simplify a number of related tasks.

Applications such as analytics tools often process data from multiple sources. When a company suspects that an application may have ingested inaccurate information, identifying the source of the issue is often a time-consuming task. The reason is it can be difficult to determine exactly what information was ingested and when.

Monte Carlo says its Data Product Dashboard eases the task. The tool makes it possible to create a technical definition that describes the data assets an application ingests. Engineers can check that definition when an information quality issue emerges to determine where they should search for the root cause.

Co-founder and Chief Technology Officer Lior Gavish (pictured) explained how the feature works in an interview on SiliconANGLE Media’s theCUBE. “They can basically go into the tool, define what constitutes the data product — what are the objects that are actually the data product, whether it’s tables or BI reports or models — and understand not just what’s going on with those specific objects but what’s going on with everything that’s upstream of them,” Gavish said. 

The Data Product Dashboard also lends itself to machine learning projects. According to Monte Carlo, the tool is capable of tracking AI models and the training datasets they use.

The tool generates metrics that describe the quality of a company’s data assets. It can highlight the number of issues that affect a certain asset, their severity and whether or not they have been fixed yet. It also provides technical information about the individual database tables that comprise a certain data asset.

The company says another benefit of the tool is that it can help engineers catch errors in datasets before business users do. “From a trust perspective there’s a huge difference between you finding out that the address was wrong versus the person who built the system for you telling you,” Gavish explained. 

The Data Product Dashboard is currently available in beta as part of Monte Carlo’s data observability platform. 

Photo: SiliconANGLE