ayazhan

good idea, we'll add db connection string to credential details.

yes, we were also thinking about converting multiple csvs into multiple table, it's on the roadmap.

thanks for suggestions!

Hey HN, we built a tool that uploads CSV files to a hosted PostgreSQL and gives you database credentials to query it. We recently built a number of database integrations for one of our products and had to manually create test databases with seed data in them. We think this would be helpful if you're building a simple web application or taking a coding course and need a quick way to add some of your own data for testing. It might also be helpful if you are running a demo/pilot with a potential customer and want to easily add a more relevant dataset for them. Give it a try and let us know if you have questions or feedback.

Thank you for recommending these! Our problems is not related to Lambda functions though, they can run for minutes. It is the API Gateway that shuts the connection after 30 seconds. We might just need to build our own web server.

Great advice! We'll give it a try, thank you!

Will do, thanks for advice!

This is cool! Our vision is to simplify this experience with intuitive visual tools and advanced features, such as versioning, data governance, saved queries, and more.

Thanks!

1. Yes, We learned that pretty quickly. Especially when working on postgres and mongoDB. And this is the value we’re trying to deliver. As a user, you don’t have to know technical differences between databases and query them all the same way.

2. Interesting idea, we’ll give it a try, thanks!

3. Yes, we don’t have an aggregate feature just yet, working on it. For large datasets, we're thinking about loading a sampled version of the dataset instead for a quick analysis (like histogram analysis and so on). Lowering default limit is interesting, but we are worried it might compromise the experience (if you can only load 10,000 out of 1,000,000 records, you might not be able to do all the analysis you want). Still exploring solutions

Yes, data is returned directly from lambda. We’re working on the pro version and enterprise versions that will run queries in the backend and update sheets as you described. For that, we’d need to request for additional scopes, to be able to update sheets remotely. Currently, updates are made by the addon and only when it is in use.

Ok, sounds good. we'll keep it generic and won't mention the source. Thank you for sharing! We think this is something AI companies can benefit from in the future.

Thanks for your feedback ohazi! You are right that “No system should ever fail silently” and there are many ways to address this. However, we’ve seen cases where not enough attention is put into input data pipelines and similar mistakes are being made by new and even well-funded AI startups. One of the reasons this is happening is because some of these startups are launched by people with little experience in machine learning / data science. For example, we’ve seen doctors, web developers, lawyers and accountants moving into AI space. They can learn the basics of machine learning and maybe hire someone to help them, but often don’t know about the best practices or things to watch out for when building a data driven company. Unfortunately, there are few guidelines or best practices available online. With this article, we were hoping to help these new AI startups by bringing awareness to the importance of data pipelines.

Thanks nostrademons, these are great examples. You're right, name and email are just for illustration. Would you mind if we use your feedback and some of your examples to improve the article? If yes, should we credit your HN account?

In this article, we showed a scenario where a small change to the front-facing interface could dramatically reduce the accuracy/performance of a machine learning model powering the application