Da

Data Infrastructure assistant for Data teams

Hacker News

Data Infrastructure assistant for Data teams

Hey HN, Hope everyone is doing great! I have built a fairly early stage prototype of something called as a Data Infrastructure Assistant - https://render-dda.onrender.com/ . Try the following prompts - ‘What is the Calculation behind metric TotalRevenue’ - ‘Calculation behind metric TotalRevenue’ - ‘In which table is the column TotalAmount’ - ‘Is there a table that contains details of an order from a customer’ Please see the problem it aims to solve and the solution, Problem : Quick and easy access to metadata (data dictionary, metric definitions) has been observed to be a challenge for data teams. Solution : With Data Infrastructure Assistant, we aim to solve the above problem (think Google/Perplexity) for your data infrastructure. Vision is, to provide quick and easy accessible information to the data teams. Under the Hood: Leveraging LLMs to access metric specific information. Description for the metric definitions is pulled off of the code written to generate the metrics. Also, this way the engineers don’t have to spend as much time on documentation. Is the problem real? Happy to get any feedback on this! Thanks and cheers!

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: google, perplexity, code · Missing: mac, agents, macos
66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google, way · Missing: mobile apps, ios, personal
21%21% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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