Better Data and Decision Making with Automatic Data Validation

Embriette Hyde

If you manage a team in R&D, you know that data integrity in process development is critical to making the right decisions quickly. Yet, data integrity is one of the major challenges facing science. Many teams have struggled to have a connected and scalable setup for checking and ensuring data integrity.

To solve these challenges, we work closely with our customers to make automatic data validation a reality in Riffyn Nexus.

This month, we announced Riffyn Nexus v4.2 — packed with features to streamline the iterative process that is central to R&D. We’re especially excited about automatic data validation, the final piece of a complete package that delivers process developers the capabilities they need to ensure data integrity in decision making.

More quality data and time saving

With automatic data validation, Riffyn Nexus takes the headache out of ensuring data integrity (and therefore, quality). Now process developers can define what should be correct, validate it real-time (3,300 samples, parameters, or measurements checked per second), and trace the root cause of exceptions. In the true spirit of iteration, users can build their knowledge upon each round of learning from experiments.

It was critical that we ensure the validation actions sacrifice no flexibility for Riffyn Nexus users. Riffyn engineers challenged themselves to design the system to dynamically accommodate process changes, deal with varied data types gracefully, handle both status and time series data equally, and assemble all of this in real-time for checking validity.

So, how does data validation work?

Data validation, despite the complexity in engineering, is simple in practice.
When designing your process in Riffyn Nexus, you’ll have mandatory fields for resource types and properties. You can define valid options for those resource types and properties as well as specification limits for numerical properties.

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Any experiment created on the process design automatically “inherits” the pre-defined, valid parameters. These parameters are used by Riffyn Nexus to perform automatic data validation. As soon as data are captured on the experiment, Riffyn Nexus runs data validation automatically Users see the invalid parameters being flagged real time, and can then investigate and fix any errors.

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Voila! That’s it! Automatically validated data.

We strive to provide our customers with the best tools possible to streamline R&D processes. API 2.0 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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