Data Science with KNIME

KNIME®with headquarters in Zurich and offices in Constance, Berlin and Austin, offers a fast, simple and intuitive entry into the field of data science with its data analysis, reporting and integration platform. The KNIME Platform integrates a wide range of data types, statistical functions and advanced prediction and machine learning algorithms. For more than a decade, a thriving community of data scientists in over 60 countries has been working with the KNIME Platform on all kinds of data: from numbers, images, and molecules to complex networks and statistics and big-data analysis.

The KNIME Analytics Platform is the leading open solution for data-driven innovation, enabling you to discover the potential hidden in data, gain new insights or predict new futures. Companies can take collaboration, productivity and performance to the next level with a number of commercial enhancements to the open source platform.

KNIME is a bundle of Eclipse software licensed under the Eclipse Public License (EPL) and separate KNIME plug-ins licensed under the General Public License (GPL), version 3 (including certain additional permissions under section 7 of the GPL).
KNIME believes in open source and the power of the community. Our open source platform contains all the features every user needs, plus advanced features. KNIME Analytics Platform does not have a slimmed down version and there are no artificial limitations, such as the size of machine processing or the number of data rows: If you have enough disk space and memory, you can run projects with hundreds of millions of rows, as many KNIME users currently do.

Data Science helps companies to gain insights, patterns and recommendations for decisions from structured and unstructured data. As a result, companies that actively use the potential of their existing and yet to be integrated data have a clear advantage over their competitors when it comes to better understanding customer concerns, reacting to new market opportunities and improving services. Investments in this area generally lead very quickly to a positive return on investment (ROI) by increasing productivity and reducing costs.

Digitization remains one of the defining trends for companies. In addition, data volumes continue to grow unabated, and this trend will continue in the near future due to the integration of more and more systems and end devices. As a result, classic methods of data analysis are reaching their limits. With the use of data science, processes can be automated, better planned and more meaningful in combination with the use of artificial intelligence. The resulting findings can be used to make decisions in real time. Data Science is a cornerstone of modern IT systems and will remain so in the future.