Dataiku Releases New Enterprise Tools to Democratize AI
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Dataiku Releases New Enterprise Tools to Democratize AI

23 Aug 2021 (Last Updated August 23rd, 2021 10:44)

Dataiku Releases New Enterprise Tools to Democratize AI
Credit: mohamed Hassan from Pixabay

Concept: NY’s enterprise AI and ML platform operator Dataiku has expanded its efforts to make AI accessible to the ordinary business user with an upgrade that allows users to perform what-if simulations of AI models to see how changes to the data they are based on would impact them. The aim, according to the startup, is to make it easier for business analysts to experiment with AI models based on machine learning algorithms that they can develop with the help of a data scientist team.

Nature of Disruption: As part of this endeavor, Dataiku 9.0 introduces the Model Assertions tool, which allows a subject matter expert to inject a known condition or sanity-checks into a model to prohibit a certain outcome or conclusion from ever being reached. There’s also a Visual ML Diagnostics tool that generates error messages if the platform predicts a model will fail, as well as a Model Fairness Report tool that gives companies access to a dashboard where they can analyze an AI model’s bias or fairness. Finally, there is also now a Smart Pattern Builder and Fuzzy Joins capability that facilitates working with more complex or even incomplete datasets without having to write code or manually clean or prep data.

Outlook: Many organizations are investing in AI to make better data-driven decisions, according to Dataiku, which necessitates business analysts creating AI models without having to wait for a data science team to do so. That doesn’t mean an organization shouldn’t engage a data science team to tackle more difficult problems, but it does lessen an organization’s reliance on a small team of specialists, the startup noted. Dataiku bills itself as an end-to-end platform for developing, deploying, and managing AI and analytics applications, including data connectors for Amazon S3, Azure Blob Storage, Google Cloud Storage, Snowflake, and NoSQL/SQL databases. The startup has raised $400mn in a Series E round of funding at a $4.6bn valuation. It claims to help “democratize AI” for enterprise clients across industries like Unilever, Westpac, OVH, NXP Merck, and Ubisoft, which leverage the platform to optimize their supply chain, lessen customer churn, identify fraud, and others.

This article was originally published in Verdict.co.uk