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Life Sciences

Make the best use of data to improve customers’ lives and also establish and maintain market leadership.

Helping life sciences get the most out of useful data

With AI and machine learning, life sciences companies are empowered to make use of all the data available to them – from research to clinical trials, the production line and customers themselves. RapidMiner’s leading data science platform helps life sciences organizations around the world improve their customers’ lives, and establish and maintain market leadership.

Life Sciences Industry Use Cases

Drive Revenue

Cut Costs

Avoid Risks

Why AI Now?

Just as the life sciences are transforming lives, the industry itself is being transformed. Competition from new start-ups and shifting regulations are creating pressure to conduct R&D and clinical trials faster, but also with more transparency and precision.

The growing levels of investment needed for successful product development and production is reducing room for error and driving a need for more certainty in every step on the path to revenue. At the same time, the growing volume of data available for research and analysis represents incredible opportunity to find new cures and exciting innovations faster than ever.

Data science can better equip life sciences companies to make the best possible use of data.

What Our Customers Say

"RapidMiner, The Dependable Friend Of The Lonely Data Scientist!"
Strategic Initiatives Manager in the Healthcare Industry
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RapidMiner really democratizes data science for citizen developers. In the past, I had experiences with some other data science platforms which were fragmented and not fun to use. RapidMiner; however, provides one platform for all stages of data science projects and all components work seamlessly with each other. The 'making it connected and work' hassle is no longer there, thanks to RapidMiner's integrated solution.

Read the full review on Gartner Peer Insights
"Excellent End-To-End Data Science And AutoML Solution"
Chief Analytics Officer in the Government Industry
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We started using RapidMiner Studio and AI Hub about 3-4 months ago. We wanted an end-to-end data science platform that could easily be configured with our legacy source data systems, as well as easy direct connections to external data sources—in addition, a product with a variety of supervised learning models which allow us to quickly iterate. RapidMiner has been excellent in that aspect.

Read the full review on Gartner Peer Insights
"RapidMiner Is Being A Great Resource In Our Data Science Journey!"
Business Excellence Regional Senior Manager in the Healthcare Industry
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RapidMiner demonstrated to be a very useful and effective tool. In addition to that, the training and support offered was outstanding, covering a variety of projects and different types of trainees. It is clearly the correct partnership to drive us on this data science journey.

Read the full review on Gartner Peer Insights
"Awesome Data Science Tool That Helps Companies Drive Business Solutions"
Data Analyst Specialist
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RapidMiner Studio is an awesome tool! It really speeds up the data exploration process and provides a firm foundation for building machine learning models. The support staff is excellent! They really helped me and my team build and prove out our use case to put into production. They also helped us integrate seamlessly with Tableau, which was critical for our user group. Overall, would highly recommend the tool to anyone who is looking at taking their predictive analytics/machine learning capabilities to the next level.

Read the full review on Gartner Peer Insights
Gartner Peer Insights reviews constitute the subjective opinions of individual end users based on their own experiences, and do not represent the views of Gartner or its affiliates.
Machine learning models that have such potential to impact your business can also be hard to explain. Here’s how to interpret and explain your models in ways that everyone can understand.

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Stop Waiting for Perfect Data

Waiting on perfect data to start a machine learning project is troublesome. Instead, ask yourself what makes data good enough for the project to have an impact. Here’s why.

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Let's talk about the ways data science can be used to improve lives, while also helping your organization drive revenue, cut costs, and avoid risks.