Umetrics Suite Blog

How principal component analysis helps optimize chemical selection for solvents, reagents and molecules

June 12, 2019

In agrochemical, pharmaceutical and other industries that manufacture complex chemicals, finding ways to reduce waste and improve inefficiencies often hinges on selecting the right chemical compounds. Data analytics can help manufacturers find alternative compounds that meet complex requirements, decrease raw material usage or enable more cost-effective, sustainable processes.

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Using data analytics techniques for text mining and analysis of patents

November 13, 2018

Mining information in unstructured text can be a real challenge. Patent documents, for example, provide a rich source of technological and scientific knowledge that can reveal technological trends as well as information on the legal landscape of the market. This makes analysis of the vast and ever-growing number of patents an important part of corporate business strategies.

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What is principal component analysis (PCA) and how it is used?

April 6, 2018

Principal component analysis, or PCA, is a statistical procedure that allows you to summarize the information content in large data tables by means of a smaller set of “summary indices” that can be more easily visualized and analyzed. The underlying data can be measurements describing properties of production samples, chemical compounds or reactions, process time points of a continuous process, batches from a batch process, biological individuals or trials of a DOE-protocol, for example.

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Why pre-processing your data creates better data analytics models

March 8, 2018

What do we mean by pre-processing of data, and why is it needed? Let's take a look at some data pre-processing methods and how they help create better models when using Principle Component Analysis (PCA) and other methods of data analytics.

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