BabelViz -Machine Translate Tableau Dashboards into over 150 Languages

Hacker News

Hey HN! I built BabelViz, a Tableau dashboard extension that translates dashboards automatically into over 150 languages. The idea came from seeing global teams wrestle with static language solutions and relentless, frustrating tweaks. Tasks like duplicating workbooks, managing calculated fields, and regression testing (since Tableau updates could alter the underlying XML structure) made localization a serious challenge. With BabelViz, translation is as simple as dragging and dropping the extension onto your dashboard. You get automatic translations, personalized language preferences that persist without users needing to change settings manually, and custom glossaries for translation overrides. This way, you retain translation control over specific terms to ensure accurate and consistent messaging for your audience. BabelViz also operates as a secure, on-premises solution for privacy and data security. Would love to hear what you think, any feedback, or questions on this. https://babelviz.com

Visit product View on Hacker NewsNov 12, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, user, tasks · Missing: agents, macos, agent

77%77% 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.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, users, way · Missing: mobile apps, ios, entrepreneurs

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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