Meet Riffyn: Analyze Mode

Last time we introduced you to Riffyn's all new Measure Mode,  where you plan and execute your experiment design and capture your data. Before that we introduced Design Mode, where you visually define how you want to achieve your scientific aims. This week we're going to talk about Analyze Mode, which equips you to clean your data, join together across process steps and instruments, and analyze it using your favorite statistical analysis packages. If you'd like to setup a demo and learn about getting a trial started please contact us!


Not everything matters. It's tempting to interpret the measured change in your output as due to the change you made deliberately to your input, yet it is often due to other changes you didn't control. Even when you could swear you changed nothing at all, the outcomes of repeated experiments usually change to some degree. And even when you make repeated measurements on the outcome of a single process instance, those measurements can vary as well.

Riffyn's Analyze mode helps you use advanced data analytics to determine what matters and how much. Not only can you determine the simplest model that explains the most intended variation, you can even parse the unexplained variation -- noise -- using Riffyn's computer-aided process design as context. Estimating these variance components helps to focus limited resources on the one or two parameters that drive most of your total process variation.


Riffyn includes several powerful procedures including data grouping, summarization, and data cleanup. Data can be grouped using exact matches or other algorithms such as K-Means Clustering, Density Based Spatial Clustering, or a Sliding Window Alignment. This makes it easy to align multiple data points that might have been measured just a few seconds apart from each other.

Data can also be summarized by mean, maximum, median, mode, or minimum values, with more to come soon. For example, in the data below three values have been measured for spectral absorbance at different time intervals. Using summarization, Riffyn can automatically calculate the mean for these readings. 

You can plot your data alongside your specifications, and identify potential patterns and outliers.

Finally, you can export your data from either a single experiment or across an entire process, formatted for easy analysis in a variety of third-party statistical analysis packages, like JMP.


Analyze Mode integrates your data across experiment, process, user, and location to drive powerful insights. 

Thanks for joining us to learn more about Analyze Mode! Next time we’ll introduce Share Mode, which allows you to collaborate within your team, your organization, and the scientific community-at-large.