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Replibyte – Seed your database with real data

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Re: Replibyte – Seed your database with real data

#11

Post by pistoriusp »

bennyp101 wrote: post #3

How does it keep personal data safe? I had a look at “how it works” and “faqs” but they don’t answer how you keep stuff safe? It also gets uploaded to S3? I might have missed it, but I need to know exactly where our PII is stored (so not on a dev laptop), how do you know what to replace and what do you do with any info you do replace? Edit: To answer my own question, via transformers. But that seems to suggest each d…

You may want to check out Snaplet at https://docs.snaplet.dev. I'm the co-founder, but we're not open-source (yet.) Our goal is to give developers a database, and data, that they can code against.

We identify PII by introspecting your database, suggest fields to transform, and provide a JavaScript runtime for writing transformations.

Besides transforming data, you can reduce, and generate data. We are most excited about data-generation!

The configuration lives in your repository, and you can capture the snapshots in GitHub Actions. So you get "gitops workflow" for data.

A typical git-ops workflow:

  1. Add a schema migration for a new column. 
  2. Add a JS function to generate new data for that column.
  3. Add core to use the new column.
  4. Later, once you have data, use the same function to transform the original value. (Or just keep generating it.)

Re: Replibyte – Seed your database with real data

#12

Post by pistoriusp »

roskilli wrote: post #5

One feature I’d love to see is a transformer that instead of providing a random value provides a cryptographic one way hash of the data (ie sha2) - that way key uniqueness stays the same (to avoid unique constraints on columns) and also the same value used in one place will match another value in another table after transformation which more accurately reflects the “shape” of the data.

We do this via Copycat (https://github.com/snaplet/copycat). We generate static "fake values" by hashing your original value to a number, and map that to a fake-value.

Re: Replibyte – Seed your database with real data

#13

Post by ev0xmusic »

bennyp101 wrote: post #3

How does it keep personal data safe? I had a look at “how it works” and “faqs” but they don’t answer how you keep stuff safe? It also gets uploaded to S3? I might have missed it, but I need to know exactly where our PII is stored (so not on a dev laptop), how do you know what to replace and what do you do with any info you do replace? Edit: To answer my own question, via transformers. But that seems to suggest each d…

Hi, author of Replibyte here :)

Yes, transformers is the way to go. I plan to add a way to detect schema changes and at list not trying to create a dump in case of change. I don't think it can be done in a safe way without human admin check.

(Thank you for your PR)

Re: Replibyte – Seed your database with real data

#14

Post by ev0xmusic »

roskilli wrote: post #5

One feature I’d love to see is a transformer that instead of providing a random value provides a cryptographic one way hash of the data (ie sha2) - that way key uniqueness stays the same (to avoid unique constraints on columns) and also the same value used in one place will match another value in another table after transformation which more accurately reflects the “shape” of the data.

Hi, author of Replibyte here. Feel free to open an issue and explain what is your use case. I will be happy to consider a solution with the community.

Re: Replibyte – Seed your database with real data

#15

Post by evoxmusic »

dopidopHN wrote: post #4

The default seems to be to store the sanitized dump on S3. It’s not always available in a professional context. Or might be considered extraction. Keeping everything local and detailing exactly what goes where and how would be helpful.

You have a local storage option https://www.replibyte.com/docs/datastores#local-disk

Re: Replibyte – Seed your database with real data

#17

Post by cratermoon »

roskilli wrote: post #5

One feature I’d love to see is a transformer that instead of providing a random value provides a cryptographic one way hash of the data (ie sha2) - that way key uniqueness stays the same (to avoid unique constraints on columns) and also the same value used in one place will match another value in another table after transformation which more accurately reflects the “shape” of the data.

What you're asking for is similar to what goes by the term "tokenization"[1], a technique often used by payment processors to avoid leaking credit card numbers and similar sensitive data. Using the proper transformer might provide the behavior you need.

1 https://www.tokenex.com/resource-center/what-is-tokenization

Re: Replibyte – Seed your database with real data

#18

Post by lstamour »

ff7c11 wrote: post #16

Trying to think how to anonymise datetimes hurts my head. You might want to randomise the date of an event. But you also need this random date to be consistent with respect to both the current time and the order of other related rows in the database.

The answer is always “it depends,” but I think if a date time is a UTC timestamp, such as a record of when an event happened, then with random sampling, it shouldn’t matter? It’s just a timestamp. The amount of information it contains might include location, might include timing to other events, could be correlated, but… on its own? It doesn’t need anonymization. Likewise the sequence of events, should be safe to use.

I get that you can look up or de-anonymize an event by its timestamp and the same is true of ID numbers. But it’s worse for ID numbers because these are often permanent and re-used for multiple events.

But yeah, the risk in anonymized data is that it’s never truly both anonymous and useful. Truly anonymous data might be considered junk or random data.

Anonymized data has some utility purpose to fulfil. Perhaps “realistic” analytics is required, or you want to troubleshoot a production issue without revealing who did what to engineers. So you anonymize the fields they shouldn’t see, and create a subset of data that reproduces the issue…?

Anonymized data is almost always a bad approach compared to generating data from algorithmic or random sources, but sometimes we need anonymized or restricted data to start that process.

Re: Replibyte – Seed your database with real data

#19

Post by BobbyJo »

lstamour wrote: post #18
ff7c11 wrote: post #16

Trying to think how to anonymise datetimes hurts my head. You might want to randomise the date of an event. But you also need this random date to be consistent with respect to both the current time and the order of other related rows in the database.

The answer is always “it depends,” but I think if a date time is a UTC timestamp, such as a record of when an event happened, then with random sampling, it shouldn’t matter? It’s just a timestamp. The amount of information it contains might include location, might include timing to other events, could be correlated, but… on its own? It doesn’t need anonymization. Likewise the sequence of events, should be safe to use…

Data can be anonymous and useful. You however have to define what you mean by useful, an use that to inform how you go about making it anonymous.

A good example is: https://gretel.ai/blog/gretel-ai-illumina-using-ai-to-create...

Full disclosure, I work at Gretel, but I thought this was relevant enough to mention.

Re: Replibyte – Seed your database with real data

#20

Post by lstamour »

BobbyJo wrote: post #19
lstamour wrote: post #18

Earlier quoted context omitted.

The answer is always “it depends,” but I think if a date time is a UTC timestamp, such as a record of when an event happened, then with random sampling, it shouldn’t matter? It’s just a timestamp. The amount of information it contains might include location, might include timing to other events, could be correlated, but… on its own? It doesn’t need anonymization. Likewise the sequence of events, should be safe to use…

Data can be anonymous and useful. You however have to define what you mean by useful, an use that to inform how you go about making it anonymous. A good example is: https://gretel.ai/blog/gretel-ai-illumina-using-ai-to-create... Full disclosure, I work at Gretel, but I thought this was relevant enough to mention.

True? But I wouldn’t call creating new data from non-anonymous data “making data anonymous”. Instead, that’s new random data whose values are constrained or based on real-world data. I’d call that newly generated data, not anonymized data.

To me, anonymized data has an inherent risk of leaking the original transaction because it is a one-to-one mapping of the original data. If you generate new data, it will by definition diverge from the production dataset in some way that might be unrealistic. For example, fields with address components might not actually point to real places, or might not be written the same way as they would be in production. Perhaps a portion of production data includes international addresses or rural routes that your software might fail to generate, or worse, maybe it would generate them incorrectly.

Frankly, generating data is a better approach than anonymized data. And I know of anonymization techniques where good data is mixed with bad data and statistically, the bad data can be filtered out later but only in aggregate, etc. But I’m drawing a line in the sand between anonymized data that closely matches real data, and that which is “generated data”, because you can still potentially learn from the anonymized data but you can’t learn from generated data much more than you would from the initial model that created the constraints used to generate the data. I’m probably explaining this poorly, it’s a bit late at night in my time zone. :)

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