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From big data to smart knowledge

The term big data seems old school now that ‘machine learning’, ‘deep learning’ and emerging concepts such as ‘edge AI’ are the hypes of the day. However, despite our general familiarity with the concept of big data, challenges related to data-driven decision-making still remain. 

Several key learnings about data have emerged over the last decade, and the tension between the culture of generating massive volumes of data and the culture of applying that data to achieve meaningful outcomes is now stronger than ever. How do we use our expensive data processing and analytics tools to generate actionable insights? Learn more in this whitepaper.

FAIR data principles

In other words, the data is: findable, accessible, interoperable, and reusable. 
This means, a.o. that each data set is registered, has unique and persistent identifier, is enriched with knowledge from ontologies and can be retrieved easily.

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What you will learn


Data-driven decision making

The challenges related to data-driven decision-making and how to overcome them.

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Achieve concrete business goals

How data can be a valuable asset to achieve concrete business goals.


Essential components of ontologies

The essential components of ontologies for data-driven decision making.

From big data to smart knowledge | Whitepaper

An added value for ...

  • VP and Head of Data Science
  • VP/Director of Biology
  • VP/Director of Research
  • Scientists
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  • Medicinal Chemists
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  • Data Scientists
  • Drug Discovery Professionals
  • Research & Development
  • Bioinformaticians
  • Professionals
  • AI / Machine Learning Professionals
  • CIO
  • CTO

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