Mastering Data Quality A Feature Deep Dive With Dataiku and Aimpoint Digital

A recent survey from Dataiku reveals that data quality challenges remain the primary factor preventing return on AI initiatives. So how can you make sure that the data used to build ML models and analytics projects is trusted, validated, and accurate?

In this webinar featuring Ben Gardner-Moss from Aimpoint Digital and Lauren Anderson from Dataiku, we will walk through some of the primary challenges associated with data quality. Hear about best practices for data quality in general, stories of success, and then deep dive into solving them with hands-on tips and tricks to show how you can solve them using Dataiku.

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[ChristianGuhr]

Intersting...reminds me of some features of JMP...which are really useful since years. Tanks for incorporating them in Dataiku.