R&D Data is Different
Scientific innovation is driven by complex data, and the research labs of today are sitting on an untapped goldmine.
That’s because R&D data has a distinct anatomy that makes unlocking its value difficult:
- R&D data doesn’t conform to a simple, singular format, but a scattered collection of images, videos, tables of values, scientific measurements and more
- The volume of R&D data can be substantial, but the actual number of applicable data points is minimal
- R&D data is easily concealed, requiring special computations to be interpreted
- The shape of R&D data in each setting evolves over time as its use cases change
General-purpose data management solutions are ill-equipped to confront the unique challenges of R&D data, leaving researchers in the dark. In R&D, data is not the byproduct of operations, but the very means of production and harnessing its value is the key to faster discovery and smarter innovation.
Enter Enthought Edge.
We’re empowering scientists to discover never-before-seen value in their R&D data. Our powerful DataOps solution enables scientists to standardize complex R&D data through Dynamic Data Modeling, access data easily through a secure central gateway, develop new data-driven insights and unlock opportunities to leverage new technologies and solutions.
Accelerate Scientific Discovery and Drive Innovation with Enthought Edge.
1m39s | Introducing Enthought Edge: Unlocking the Value in Your R&D Data
One centralized database tailored to the needs of R&D data and an intuitive search interface to find and use R&D data easily, efficiently, and securely. Empower scientists to spend less time looking for data, and more time developing solutions.
The shape of R&D data evolves frequently as scientists work on new research problems. Edge provides the flexibility and scalability scientists need — no more worrying about data migrations and wasting time doing mundane data wrangling.
Preparing data for analysis can take more than 80% of the time spent in AI/ML projects. Edge stores your data in an analysis ready-form. The integrated Jupyter environment:
- Allows scientists to directly work with data and perform AI/ML studies.
- Removes last-mile barriers between scientists and raw cloud resources (storage, compute, collaboration) to unlock the value of your cloud investments.
- Supports the end-to-end lifecycle of data applications from the prototyping stage all the way to productionization– scale faster with Edge.