Highlights:

  • In a multifaceted analytics dashboard, a slight undercount of in-store sales by one or two percentage points within a pie chart could easily elude detection for days. Specific issues, like outdated database tables, pose even more significant challenges in detection.
  • As per the company, its software can assist developers in identifying data quality issues before they are deployed to production. Additionally, the platform generates remediation suggestions to expedite the troubleshooting process.

Foundational Data Inc., a startup aiding enterprises in safeguarding the accuracy of their internal datasets, disclosed raising USD 8 million to fuel its growth initiatives.

Viola Ventures and Google LLC’s Gradient Ventures fund spearheaded Foundational Data’s seed funding round. Joining the seed round were executives from Meta Platforms Inc., Datadog Inc., and other prominent tech firms. In conjunction with the investment, Foundational Data announced the official launch of its namesake platform, offering widespread availability for troubleshooting data quality issues.

Identifying inaccuracies in business information can be challenging since their impact is frequently confined in scope. In a multifaceted analytics dashboard, a slight undercount of in-store sales by one or two percentage points within a pie chart could easily elude detection for days. Specific issues, like outdated database tables, pose even more significant challenges in detection.

Once engineers identify a data quality issue, pinpointing its root cause can be complex. This complexity arises because each malfunction typically has multiple potential causes. For instance, a duplicate row could originate from either erroneous data entry or a faulty update to the database’s settings, highlighting the multifaceted nature of the issue.

Alon Nafta, Co-founder and Chief Executive Officer of Foundational stated, “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? 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 pledges to streamline the process of resolving such issues. As per the company, its software can assist developers in identifying data quality issues before they are deployed to production. Additionally, the platform generates remediation suggestions to expedite the troubleshooting process.

The platform operates by mapping out all the code interacting with a company’s datasets.
It can detect SQL queries, Apache Spark analytics workflows, and the ETL pipelines that transfer information between a company’s applications. Subsequently, Foundational identifies code snippets that may introduce errors into the data.

Additionally, it generates a log of all changes made to a given database. When confronted with a quality issue, developers can refer to the log to identify the change responsible for the problem.

Foundational asserts that its platform is well-suited for a variety of related tasks. It can lower infrastructure costs by identifying redundant code assets, such as obsolete data processing scripts, that should be disabled—foundational flags datasets containing sensitive information, aiding customers in ensuring compliance with relevant cybersecurity requirements during processing.

The company reports that since its launch in 2022, it has analyzed over 60,000 code changes for developers. Foundational’s clientele comprises publicly-traded insurance provider Lemonade Inc. and various venture-backed startups. To bolster its market presence, Foundational Data’s seed funding round proceeds will be used to enhance its platform and amplify customer acquisition endeavors.