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Despite the increased investment in machine learning and AI technologies, many businesses have yet to see significant ROI on these projects.

The simple fact of the matter is that data science inefficiencies are holding companies back, as the average data scientist is spending 50% to 80% of their time wrangling data instead of building and using models with that data.

So how can organizations govern unruly data, reform ineffective processes, and ensure models reach production?

Read this white paper to learn how you can reevaluate your approach to analytics and data science models, allowing you to deploy real-time, advanced AI analytics that capitalize on your AI investments.

Vendor:

Teradata

Posted:

Aug 26, 2021

Published:

Jun 17, 2021

Format:

PDF

Type:

White Paper