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Final Up to date on July 15, 2022
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In case you’re a knowledge engineer or knowledge scientist, you know the way onerous it’s to generate and keep reasonable knowledge at scale. And to ensure knowledge privateness safety, along with all of your day-to-day tasks? OOF. Discuss a heavy raise.
However in at present’s world, environment friendly knowledge de-identification is not elective for groups that must construct, check, resolve, and analyze in fast-paced environments. The rise in ever-stronger knowledge privateness laws make de-identification a requirement, and the growing complexity and scale of at present’s knowledge make de-identifying it a monumental problem. Many groups attempt to deal with this in home…and lose hours out of their day consequently, solely to search out that their generated knowledge isn’t reasonable sufficient for efficient use.
There’s a higher means, Djinn by Tonic.ai.
As a substitute of cumbersome workarounds or outdated legacy instruments, get a platform constructed to work with and mimic at present’s knowledge whereas integrating seamlessly into your current workflows. Tonic.ai’s artificial knowledge options allow you to create high-fidelity knowledge that’s helpful, secure, and simple to supply—and it meets the wants of each knowledge scientists and knowledge engineering alike.
Djinn by Tonic.ai gives knowledge groups:
Built-in Workflows
- Practice fashions inside Djinn to hydrate ML workflows with reasonable artificial knowledge
- Work throughout databases to construct personalized views and export instantly into Jupyter notebooks
Knowledge Constancy
- Seize advanced relationships inside your knowledge throughout interdependent columns and rows
- Make use of deep neural community generative fashions on the innovative of information synthesis
Knowledge Privateness
- Acquire confidence in your knowledge’s privateness and in your mannequin’s suitability for ML functions
- Validate the privateness of your knowledge with comparative experiences inside your Jupyter pocket book
Platform Options
- Hook up with main relational databases and knowledge warehouses. Streamline and maximize your workflows by way of API
- Really feel safe figuring out that your knowledge by no means leaves your surroundings
Make the most of your current knowledge whether or not or not it’s for testing, coaching ML fashions, or unlocking knowledge evaluation. Reply nuanced scientific questions, allow higher testing, and help enterprise selections with the artificial knowledge that appears, feels, and behaves like your manufacturing knowledge – as a result of it’s produced from your manufacturing knowledge. For extra info or a demo, go to our web site. In case you’d prefer to give the platform a check run your self, we provide that too.
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