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DriftDB: Visualize Metric Impact Between Measurements

Hacker News

DriftDB: Visualize Metric Impact Between Measurements

Hey HN, I've been working on a project called DriftDB which helps visualize how a specific metric has changed between two measurements. If you've ever struggled with understanding the impact or shift in data metrics, this tool might be of interest! Key Features: - load your data (from a CSV) then make a change in that data and reload it - Display waterfall chart of the evolution of a measure. Installation: pip install driftdb driftdb seed create driftdb seed update driftdb start Coming features: - display lineage https://app.data-drift.io/42527392/Lucasdvrs/dbt-datagit/ove... - add insertion from dbt-snapshot

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual · Missing: mac, agents, macos
76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: visualize · Missing: mobile apps, ios, personal
62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
43%43% 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
28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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