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I still wonder who the audience is for tools like this. The website posits you can answer data questions without going through an analyst, but the role of the a

I still wonder who the audience is for tools like this. The website posits you can answer data questions without going through an analyst, but the role of the analyst is not to be a SQL whisperer for PMs and Executives - it is to be an expert in the model and the data. A data warehouse of any real scale is going to have some amount of issues - anomalous data, different interpretations of the same numbers - how does the LLM deal with that consistently across a business?

saigal 2y ago
the target audience is developers who wish to embed text to SQL functionality into their own products. the target audience is less the 'internal use case' (i.e. a data analyst) and more about letting external users do things they couldn't do before. a good example is payroll software where this type of technology can allow users to pull reports.
- arrosenberg 2y ago
  I agree that is a more reasonable use-case. The readme for this tool seems geared toward the business of answering business questions.
  - saigal 2y ago
    Tbh the original intention was to be the "data analyst" but we found over time (and with literally 100s of user conversations at small cos and enterprises) the embedded use case was more interesting and made for a better business, which was not at all what we expected.
    - rkuodys 2y ago
      Could you share how products integrate txt to sql within a product? Very curious
      - saigal 2y ago
        Search bar within the SaaS interface that allows user to ask data questions and returns back NL answer or specific cut of data
  - tirumaraiselvan 2y ago
    Why do you think that's more reasonable :) To me it seems a more risky use-case since you don't have control/observability over what an untrusted user is asking for?
- greenavocado 2y ago
  > the target audience is developers who wish to embed text to SQL functionality into their own products Who is asking?
  - boredemployee 2y ago
    you wouldnt believe the amount of developers that don't know how to write sql
    - threeseed 2y ago
      Because ORM libraries were invented 30 years ago. There is no requirement to learn SQL for most of the applications built today.
      - sfn42 2y ago
        ORM doesn't really excuse you from understanding what's going on. In a way using ORM is more difficult because you have to understand both what sql you want and how to get the framework to generate it for you. Of course there's a lot of incompetent people who have no idea what they're doing, if it seems to work they ship it. That leads to a lot of nonsensical bullshit and unnecessarily slow systems.
      - lelanthran 2y ago
        > Because ORM libraries were invented 30 years ago. > There is no requirement to learn SQL for most of the applications built today. In the same way that because Linked List libraries were invented 50 years ago, there is no requirement to learn what linked lists are for most of the applications built today? You aren't getting past the requirement to learn relational databases "because ORM", and there is no material or course that teaches relational databases without teaching SQL. The unfortunate result of this is that people who boast about knowing $ORM while not knowing SQL have never learned relational databases either.
      - meekaaku 2y ago
        Most applications dont need to get data from a relational database. But for those apps that do, knowing SQL is pretty much a must have. The developer himself or someone on the team.
- TheRealPomax 2y ago
  With what level of accuracy? And what guarantee of correctness? Because a report that happens to get the joins wrong once every 1000 reports is going to lead to fun legal problems. You still need someone who understands why you should use which approach to get the data you need without getting completely wrong numbers back that _look_ perfectly fine but reflect fantasy, not reality.
  - saigal 2y ago
    i agree that there will be "early adopter" type use cases and others that might take a while (e.g. healthcare with hipaa compliance) it is still the early days. goal is to give the developer tools to do this easier.
    - chx 2y ago
      Enough of this weasel talk. It's not the early days. Not by a country mile. To quote Cory Doctorow > I don’t see any path from continuous improvements to the (admittedly impressive) ”machine learning” field that leads to a general AI any more than I can see a path from continuous improvements in horse-breeding that leads to an internal combustion engine. You can counter it doesn't necessarily need an AGI here but that doesn't change the fact you can't crank this engine harder and expect it to power an airplane. And, as always https://hachyderm.io/@inthehands/112006855076082650 https://hachyderm.io/@inthehands/112006855076082650 > You might be surprised to learn that I actually think LLMs have the potential to be not only fun but genuinely useful. “Show me some bullshit that would be typical in this context” can be a genuinely helpful question to have answered, in code and in natural language — for brainstorming, for seeing common conventions in an unfamiliar context, for having something crappy to react to. > Alas, that does not remotely resemble how people are pitching this technology.
      - warkdarrior 2y ago
        Indeed, AI is not marketed as a BS generator, just as HTTP is not marketed as a spam/ad/fraud/harassment transport protocol. All technologies are dual-use, deal with it!
hackernewds 2y ago
This is the grievance I have as a data scientist. It is one of the fields where things are technical, while meanwhile everyone thinks they could do the job and provide excessive input and exact direction.
- saigal 2y ago
  there is a middle ground here. the most complicated queries will need the intel and business context of a smart data scientist. there are however so many types of queries where automation would make the world so much easier and allow more self-serve type data inquiries. too often the rhetoric around these topics is binary as in "it works" or "it doesn't work." in reality, there are certain use cases that work now and others that don't yet.

saigal 2y ago

the target audience is developers who wish to embed text to SQL functionality into their own products. the target audience is less the 'internal use case' (i.e. a data analyst) and more about letting external users do things they couldn't do before. a good example is payroll software where this type of technology can allow users to pull reports.

arrosenberg 2y ago
I agree that is a more reasonable use-case. The readme for this tool seems geared toward the business of answering business questions.
- saigal 2y ago
  Tbh the original intention was to be the "data analyst" but we found over time (and with literally 100s of user conversations at small cos and enterprises) the embedded use case was more interesting and made for a better business, which was not at all what we expected.
  - rkuodys 2y ago
    Could you share how products integrate txt to sql within a product? Very curious
    - saigal 2y ago
      Search bar within the SaaS interface that allows user to ask data questions and returns back NL answer or specific cut of data
- tirumaraiselvan 2y ago
  Why do you think that's more reasonable :) To me it seems a more risky use-case since you don't have control/observability over what an untrusted user is asking for?
greenavocado 2y ago
> the target audience is developers who wish to embed text to SQL functionality into their own products Who is asking?
- boredemployee 2y ago
  you wouldnt believe the amount of developers that don't know how to write sql
  - threeseed 2y ago
    Because ORM libraries were invented 30 years ago. There is no requirement to learn SQL for most of the applications built today.
    - sfn42 2y ago
      ORM doesn't really excuse you from understanding what's going on. In a way using ORM is more difficult because you have to understand both what sql you want and how to get the framework to generate it for you. Of course there's a lot of incompetent people who have no idea what they're doing, if it seems to work they ship it. That leads to a lot of nonsensical bullshit and unnecessarily slow systems.
    - lelanthran 2y ago
      > Because ORM libraries were invented 30 years ago. > There is no requirement to learn SQL for most of the applications built today. In the same way that because Linked List libraries were invented 50 years ago, there is no requirement to learn what linked lists are for most of the applications built today? You aren't getting past the requirement to learn relational databases "because ORM", and there is no material or course that teaches relational databases without teaching SQL. The unfortunate result of this is that people who boast about knowing $ORM while not knowing SQL have never learned relational databases either.
    - meekaaku 2y ago
      Most applications dont need to get data from a relational database. But for those apps that do, knowing SQL is pretty much a must have. The developer himself or someone on the team.
TheRealPomax 2y ago
With what level of accuracy? And what guarantee of correctness? Because a report that happens to get the joins wrong once every 1000 reports is going to lead to fun legal problems. You still need someone who understands why you should use which approach to get the data you need without getting completely wrong numbers back that _look_ perfectly fine but reflect fantasy, not reality.
- saigal 2y ago
  i agree that there will be "early adopter" type use cases and others that might take a while (e.g. healthcare with hipaa compliance) it is still the early days. goal is to give the developer tools to do this easier.
  - chx 2y ago
    Enough of this weasel talk. It's not the early days. Not by a country mile. To quote Cory Doctorow > I don’t see any path from continuous improvements to the (admittedly impressive) ”machine learning” field that leads to a general AI any more than I can see a path from continuous improvements in horse-breeding that leads to an internal combustion engine. You can counter it doesn't necessarily need an AGI here but that doesn't change the fact you can't crank this engine harder and expect it to power an airplane. And, as always https://hachyderm.io/@inthehands/112006855076082650 https://hachyderm.io/@inthehands/112006855076082650 > You might be surprised to learn that I actually think LLMs have the potential to be not only fun but genuinely useful. “Show me some bullshit that would be typical in this context” can be a genuinely helpful question to have answered, in code and in natural language — for brainstorming, for seeing common conventions in an unfamiliar context, for having something crappy to react to. > Alas, that does not remotely resemble how people are pitching this technology.
    - warkdarrior 2y ago
      Indeed, AI is not marketed as a BS generator, just as HTTP is not marketed as a spam/ad/fraud/harassment transport protocol. All technologies are dual-use, deal with it!

hackernewds 2y ago

This is the grievance I have as a data scientist. It is one of the fields where things are technical, while meanwhile everyone thinks they could do the job and provide excessive input and exact direction.

saigal 2y ago
there is a middle ground here. the most complicated queries will need the intel and business context of a smart data scientist. there are however so many types of queries where automation would make the world so much easier and allow more self-serve type data inquiries. too often the rhetoric around these topics is binary as in "it works" or "it doesn't work." in reality, there are certain use cases that work now and others that don't yet.