dbtPulse

Inspiration

What inspired me was learning about data, since I'm a chemical engineer, I'm in the midst of a career transition, and I want to start my own startup.

What it does

The data team wastes many hours entering data into DBT that Datahub already knows is an error. dbtPulse runs the query in Datahub before making the code.

How I built it

I followed the Datahub documentation for installation. I used Grok and ChatGPT as teachers and guides, asking them to break it down into two parts: first, I asked them to explain the challenge in simple terms and tell me how to approach it. The second part was a step-by-step guide for me to build the AI agent. I used Cursor, Trae AI, and GLM to build the AI agent and refactor the project cleanly. I’d like to thank Grok and ChatGPT for walking me through the steps and helping me when I was stuck.

Challenges I ran into

The challenge I faced was related to the setup and the code, but Grok helped me get around most of it.

Accomplishments that I proud of

Since I'm not from the data field, I'm really happy that I was able to build something of this caliber that actually works.

What I learned

I've learned how to use Grok and DataHub more effectively, and I feel ready to take on new challenges

What's next for dbtPulse

The next step for dbtPulse is to implement it so that data engineers can use it with their data and dbt.

Built With

• chatgpt
• cursor
• datahub
• glm
• grok
• trae