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Show HN: Select Star – Automated data catalog and discovery for modern data

selectstar.com

17 points by bimil 4 years ago · 4 comments

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bimilOP 4 years ago

Hello HN!

I’m Shinji, founder of Select Star. Starting today, we’re opening Select Star as a GA product with a Free tier.

HN is special to me & Select Star because I met one of my founding engineers from the HN Seeking freelancer post. He’s now built our Rust SQL parser from the ground up.

Select Star was born from my love of working with data. Over the last 13 years, I’ve worked as a software engineer, data scientist, business analyst, product manager, and a data startup founder, working with structured and unstructured data across a variety of use cases.

While having lots of data is great, I believe that to use it effectively you also need to understand the context around it. And building and maintaining that context is hard if you were to build a data dictionary manually.

Select Star is designed to bring you and everyone on your team the full context of data in your organization. Select Star will tell you where the data came from, who’s using it, how they’re using it and what reports/dashboards are already created based on the data.

And it does it automatically within the first hours of you connecting your data warehouse and/or BI tools.

See Select Star in action: https://youtu.be/eZuIyq4DP1o

Feel free to ask me anything!

tj92 4 years ago

This looks cool! What integrations do you support?

  • bimilOP 4 years ago

    Thanks! Currently we support all major cloud data warehouses and BI tools including Snowflake, BigQuery, Redshift, Tableau, Mode, Looker, and dbt.

pkuczynski 4 years ago

Hey HN,

Przemek here, Shinji's coworker at Select Star and ex-employee of YC backed startup (EasyEmail / Point). It's really exciting to share our latest project here, with such a great community.

We've put a great deal of effort making sure Select Star solves a lot of data cataloguing and discoverability problems with our design partners as well as during private beta when we worked with many many users to see how to efficiently surface an enormous amount of information that data engineers/scientists/analysts work with everyday.

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