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The blog post, demo, and website are incredibly uninformative (maybe informative, but not on own product's details). Eventually, pressing on "getting started" goes to a sign up for updates page.
The PySyft project is well-documented and researched if you want to learn about the technology.
Interesting. Is the API hosted with Sarus supposed to be used by in-house analysts? Or 3rd party? > Our key contribution is to bundle everything into an API that can be queried without seeing the data in the first place. Without being seen by who?
A big innovation is that, with Sarus, the data practitioner does not need to see the data and can still manipulate it. Most DP libraries are designed for researchers that have access to the data. They can prepare the data however they like, tune the libraries all they want, and eventually use the library to produce protected outputs from the data. With Sarus, someone who never saw the data, can achieve the same.
1. How well does Sarus work with data that is not in a database, like unstructured data such as documents/text?
2. How does Sarus handle 'legacy' DB's, where the schema for a table might not be quite right, but due to operational constraints these schemas can't be easily corrected? The canonical example I'm thinking of is date times that have been specified as strings and no one bothered to change them.
3. What kind of language support exists for interacting with the Sarus proxy? Obviously, you have Python support but for large enterprises that might need Sarus oftentimes there are a few languages that are popular internally and all need equal support. I think the comprehensive list of analytics languages in use in large orgs would look something like, [python, R, Julia, Matlab, SAS]. Rust/C++ support would be ideal as well as they're commonly used in Python/R to accelerate hot code. Do you have plans to develop SDK's? Would they be hand crafted or do you plan to develop generated SDK's similar to how GCP does it?
4. Are you moving to get any security certs? Of course you're a startup right now, but I know from experience enterprise orgs will still blindly ask questions like, "Are you FedRamp Moderate/High certified?" (This doesn't even make sense for your sales model and I'm certain you'll still have to answer this question and explain why over and over.) or "Do you have a Soc 2 Type 2 report we can look at?". The orgs that actually need something like this are going to be asking these questions pretty quickly.
5. When I use Sarus, do I have to use your IDE/interface? One of the things I noticed when looking at your demo gifs is there is a lot of use of notebooks, which of course are popular, but you'll be met with a lot of resistance if your users can't use the tooling they prefer (PyCharm Pro / DataGrip plugin to interact with DB's in my teams case).
6. How exactly is Sarus deployed? Terraform? Is it a containerized application? Does it scale vertically or horizontally? Can its logging mechanism integrate with StackDriver, Splunk, or Cloudtrail?
7. Have you proved out the technology with more complex time series data? I'm thinking of sensitive trading data.
8. Do you provide benchmarks for showing that a model trained on a real dataset is equivalent in performance a model trained on the synthetic dataset?
Super cool product and you're in a great position to make a ton of money if you nail the execution and get some large customers!
Very interesting indeed. I read that Sarus has been designed with Data Scientists persona in mind. Would that also be easily solving internal access for other engineering teams. Basically, allowing engineering teams create new features including all the local/staging/production environments sensitive data masking? Is the Sarus approach also validated by Privacy or Security authorities?
Differential privacy provides much better protection than data masking, but most importantly, it does not require any manual decision (which column to mask, how, etc.). This is what makes it easy to apply at scale to all datasets in the data warehouse or data lake instead of having dataset per dataset decision making involved.
Differential privacy is used by Apple, Google, Microsoft, or the US Census. When used properly, the data protection it provides does not need to be proven to regulators or security teams anymore. That being said, regulators do not require DP protection per se. They require organizations to put in place the best practices in terms of data governance, data minimization, or data security as a whole. This is part of the answer.
The blog post, demo, and website are incredibly uninformative (maybe informative, but not on own product's details). Eventually, pressing on "getting started" goes to a sign up for updates page.
The PySyft project is well-documented and researched if you want to learn about the technology.
Earlier quoted context omitted.
The PySyft project is well-documented and researched if you want to learn about the technology.
Is PySyft used under the hood?
The blog post, demo, and website are incredibly uninformative (maybe informative, but not on own product's details). Eventually, pressing on "getting started" goes to a sign up for updates page.
The first link is the corporate website, it may not include all the product details you expected, sorry about that. You should get a lot more details on how it works if you try the tutorial and play with it yourself. This is at the bottom of the post, hopefully it satisfies your curiosity but happy to answer outstanding questions here of course.
(As far as I'm concerned, if the answer is yes to both, this has much potential. I'm just trying to figure out what I'm looking at)
Thank you!
[1]: https://blog.openmined.org/duet-demo-how-to-do-data-science-...
Very interesting indeed. I read that Sarus has been designed with Data Scientists persona in mind. Would that also be easily solving internal access for other engineering teams. Basically, allowing engineering teams create new features including all the local/staging/production environments sensitive data masking? Is the Sarus approach also validated by Privacy or Security authorities?
Sarus is designed for all data use cases, provided that access to a given user's information is not the objective. This is the case for all of BI, analytics, or machine learning. It also works for testing or debugging, building APIs, etc. It resonates with organizations' aspiration for the democratization of data. Differential privacy provides much better protection than data masking, but most importantly, it does no…