Get to Machine-Learning Ready Data Faster with Export Subsetting

Embriette Hyde

To make machine learning a reality for rapid process improvement, data needs to be in a usable format for analysis. For years, Riffyn Nexus has simplified R&D data contextualization and formatting for machine learning and visualization.

But as any Riffyn Nexus user knows, tables of exported data can sometimes be overwhelming with columns after columns of data that you don’t necessarily need for your analysis. It can take some time to manually subset the data after export.

To give our users the flexibility to cherry-pick the experiment data sets of a process to export, we recently launched the Export Subsetting feature in Riffyn Nexus v4.2.

How does it work?

In the Riffyn Nexus UI, users can choose to export a single experiment or a subset of experiments, instead of the previous default of exporting every single experiment on a process. You can still export all experiments from a process if you choose to, and you can choose the subset of columns that you want to export. So, with just a few mouse clicks, data are subset upon export.

Say hello to even more time savings!

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Go big and go fast

Our users often produce thousands of data points. To avoid slow export of large datasets (GBs), we’ve improved Riffyn Nexus’ ability to export large datasets and enabled parallelization to reduce its export time. Now you can get to work analyzing your data even faster than before!

At Riffyn, we strive to provide our customers with the best tools possible to streamline R&D processes. Export Subsetting is one of the new features in Riffyn Nexus v4.2. The recently launched Riffyn Nexus v4.2 is packed with features to enable process developers to achieve faster process improvement. Other new v4.2 features include:

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