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Launching a Free DataOps Platform

Hacker News

Launching a Free DataOps Platform

Hey everyone, we've been developing a DataOps platform for almost a decade and it's currently used by companies like ProductBoard, Erste Bank, Home Credit, and many others. But, talking with prospects, we realized it's time to roll out a free tier of our platform. At this point, we'd just like for data teams/individuals to try it out and leave a valuable feedback. If you do love it though, you can always add more projects by purchasing additional credits. However, feel free to use our free tier as long as you need it (+ we won't ask you for your credit card info). What is this DataOps platform? It's a multi-cloud platform which unifies data management, collection, governance, pipeline automation, and sharing of data. Do you need your own database/dwh? No, it's included in the free tier. What features does it offer? We prepared a special page for this one: https://www.keboola.com/paygo/data-scientists Can I learn more about the freemium tier? https://www.keboola.com/blog/run-projects-in-keboola-connection-for-free I'm here for all your questions and feedback. Thanks!

Visit productView on Hacker NewsOct 15, 2020
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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
72%72% 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 · Missing: mac, agents, macos
60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, pipe, io · Missing: https docs, excited, just released
46%46% 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 · Strong signals: platform · Missing: plus, intuitive, reviews
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
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.

Correct prediction on native model

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