Whitepaper - 7 best practices for rolling out
from Data Products

In this white paper, we show the reasons why so many data science projects currently fail in the deployment phase. We define deployment as the moment when a proof of concept or pilot project becomes a data product to be integrated into business operations. We looked at different variants of technical deployment of data science projects and identified five basic challenges.

Content of the white paper

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Intro | Mangement Summery

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Why is this so important to us?
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What does it mean to roll out a data science project?
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Deep Dive: Technical roll-out of ML models
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Why is it so difficult to create added value with data science projects?
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Solutions and best practices
Rolling out Data Products_Whitepaper

Your added values

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Unique

Get insights from going live with over 1,000 Data & AI projects over the last 7 years.

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Innovative

Artificial intelligence and machine learning are disruptive technologies. With our data products, you can revolutionise society.

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Free of charge

We share our knowledge with you. Benefit from our experience - without compromise.

7 Best Practices Whitepaper
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