Foundational Data Inc., a startup helping enterprises ensure their internal datasets are accurate, today announced that it has raised $8 million to finance growth initiatives. 

Viola Ventures and Google LLC’s Gradient Ventures fund led the seed round. They were joined by executives from Meta Platforms Inc., Datadog Inc. and other major tech firms. Against the backdrop of the investment, Foundational Data today announced the general availability of its namesake platform for troubleshooting data quality issues. 

Inaccuracies in business information are tricky to spot because their scope is often limited. In an analytics dashboard that contains multiple graphs, a pie chart that undercounts store sales by one or two percentage points might go undetected for days. Some types of issues, such as out-of-date database tables, are even more difficult to spot.

After engineers detect a data quality problem, finding the root cause can likewise be complicated. The reason is that each malfunction often has multiple potential causes. A duplicate row, for example, might be just as likely to stem from erroneous data entry as a faulty update to the database’s settings.

 “It has become a remarkably difficult task for developers to confirm crucial questions like, ‘What dashboards will this schema change affect?,’ ‘Can I deploy this code change safely?’ or ‘What data pipelines do we have that are not working?,’” said Foundational co-founder and Chief Executive Officer Alon Nafta (pictured, front row center). “The inability to validate simple code changes, and the lack of visibility and controls, and the time-consuming nature of data engineering create a dramatic bottleneck on innovation.”

Foundational’s platform promises to ease the task of fixing such issues. According to the company, its software can help developers spot data quality issues before they’re rolled out to production. The platform also generates remediation suggestions to speed up the troubleshooting process.

The platform works by mapping out all the code that interacts with a company’s datasets. The platform can detect SQL queries, Apache Spark analytics workflows and the ETL pipelines responsible for moving information between a company’s applications. From there, Foundational identifies code snippets with the potential to introduce errors into the data.

It also generates a log of all the changes that were made to a given database. When a quality issue emerges, developers can review the log to determine which specific change caused the issues.

Foundational says that its platform also lends itself to a number of related tasks. It can reduce infrastructure costs by identifying unnecessary code assets, such as out-of-date data processing scripts, that should be disabled. Additionally, Foundational flags datasets that contain sensitive information to help customers ensure they’re processed in accordance with the relevant cybersecurity requirements.

The company says that it has analyzed more than 60,000 code changes for developers since launching in 2022. Foundational’s customer base includes publicly traded insurance provider Lemonade Inc. as well as multiple venture-backed startups. To further grow its market presence, Foundational will use the proceeds from its seed round to enhance its platform and expand customer acquisition efforts. 

Photo: Foundational