home.social

#datavalidation — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #datavalidation, aggregated by home.social.

fetched live
  1. Ah, the thrilling world of #Clojure, where a minor version update gets its own parade 🚀. And, lo and behold, checked keys are here, because nothing screams #innovation like finally adding basic data validation in 2026. 🎉 Clojure: boldly going where most languages already went. 🦖
    clojure.org/news/2026/07/02/cl #ClojureUpdate #DataValidation #ProgrammingLanguages #TechNews #HackerNews #ngated

  2. Ah, the thrilling world of #Clojure, where a minor version update gets its own parade 🚀. And, lo and behold, checked keys are here, because nothing screams #innovation like finally adding basic data validation in 2026. 🎉 Clojure: boldly going where most languages already went. 🦖
    clojure.org/news/2026/07/02/cl #ClojureUpdate #DataValidation #ProgrammingLanguages #TechNews #HackerNews #ngated

  3. Ah, the thrilling world of #Clojure, where a minor version update gets its own parade 🚀. And, lo and behold, checked keys are here, because nothing screams #innovation like finally adding basic data validation in 2026. 🎉 Clojure: boldly going where most languages already went. 🦖
    clojure.org/news/2026/07/02/cl #ClojureUpdate #DataValidation #ProgrammingLanguages #TechNews #HackerNews #ngated

  4. Ah, the thrilling world of #Clojure, where a minor version update gets its own parade 🚀. And, lo and behold, checked keys are here, because nothing screams #innovation like finally adding basic data validation in 2026. 🎉 Clojure: boldly going where most languages already went. 🦖
    clojure.org/news/2026/07/02/cl #ClojureUpdate #DataValidation #ProgrammingLanguages #TechNews #HackerNews #ngated

  5. Ah, the thrilling world of #Clojure, where a minor version update gets its own parade 🚀. And, lo and behold, checked keys are here, because nothing screams #innovation like finally adding basic data validation in 2026. 🎉 Clojure: boldly going where most languages already went. 🦖
    clojure.org/news/2026/07/02/cl #ClojureUpdate #DataValidation #ProgrammingLanguages #TechNews #HackerNews #ngated

  6. Reliable business insights via b2b data aggregation

    Accurate business data supports analytics, outreach, and planning. Data aggregation for b2b companies centralizes information from diverse sources and validates accuracy through structured checks. Continuous enrichment ensures datasets remain reliable and up to date.

    Know more: hitechdigital.com/b2b-data-agg

    #B2BDataAggregation #DataAggregationServices #DataEnrichment #DataCleansing #DataValidation #B2BDataSolutions #DataQualityManagement

  7. marmelab web developer Thiery Michel shares in this article his use of PostgreSQL features that allow us to draw certain data validation logic away from the application layer, and into the database. The proposed solutions in some instances can be more elegant than a purely application layer data validation approach.

    "9 Advanced PostgreSQL Features I Wish I Knew Sooner"

    marmelab.com/blog/2026/02/23/d

    #programming #sql #postgresql #database #datavalidation

  8. marmelab web developer Thiery Michel shares in this article his use of PostgreSQL features that allow us to draw certain data validation logic away from the application layer, and into the database. The proposed solutions in some instances can be more elegant than a purely application layer data validation approach.

    "9 Advanced PostgreSQL Features I Wish I Knew Sooner"

    marmelab.com/blog/2026/02/23/d

    #programming #sql #postgresql #database #datavalidation

  9. marmelab web developer Thiery Michel shares in this article his use of PostgreSQL features that allow us to draw certain data validation logic away from the application layer, and into the database. The proposed solutions in some instances can be more elegant than a purely application layer data validation approach.

    "9 Advanced PostgreSQL Features I Wish I Knew Sooner"

    marmelab.com/blog/2026/02/23/d

    #programming #sql #postgresql #database #datavalidation

  10. marmelab web developer Thiery Michel shares in this article his use of PostgreSQL features that allow us to draw certain data validation logic away from the application layer, and into the database. The proposed solutions in some instances can be more elegant than a purely application layer data validation approach.

    "9 Advanced PostgreSQL Features I Wish I Knew Sooner"

    marmelab.com/blog/2026/02/23/d

    #programming #sql #postgresql #database #datavalidation

  11. marmelab web developer Thiery Michel shares in this article his use of PostgreSQL features that allow us to draw certain data validation logic away from the application layer, and into the database. The proposed solutions in some instances can be more elegant than a purely application layer data validation approach.

    "9 Advanced PostgreSQL Features I Wish I Knew Sooner"

    marmelab.com/blog/2026/02/23/d

    #programming #sql #postgresql #database #datavalidation

  12. Learn how developers use data validation APIs to verify emails, addresses, phone numbers, and identities to improve data quality, security, and app performance. hackernoon.com/apis-for-data-v #datavalidation

  13. Learn how developers use data validation APIs to verify emails, addresses, phone numbers, and identities to improve data quality, security, and app performance. hackernoon.com/apis-for-data-v #datavalidation

  14. Learn how developers use data validation APIs to verify emails, addresses, phone numbers, and identities to improve data quality, security, and app performance. hackernoon.com/apis-for-data-v #datavalidation

  15. Learn how developers use data validation APIs to verify emails, addresses, phone numbers, and identities to improve data quality, security, and app performance. hackernoon.com/apis-for-data-v

  16. Learn how developers use data validation APIs to verify emails, addresses, phone numbers, and identities to improve data quality, security, and app performance. hackernoon.com/apis-for-data-v #datavalidation

  17. Just finished watching @rich_i 's great workshop about hist {pointblank} R package / python module, presented at @rinpharma 2025. Highly recommended if you deal with tabular data and need validation or beautiful summary HTML tables: youtu.be/abvgK9VU7z0 #RStats #python #DataValidation

  18. Just finished watching @rich_i 's great workshop about hist {pointblank} R package / python module, presented at @rinpharma 2025. Highly recommended if you deal with tabular data and need validation or beautiful summary HTML tables: youtu.be/abvgK9VU7z0 #RStats #python #DataValidation

  19. Just finished watching @rich_i 's great workshop about hist {pointblank} R package / python module, presented at @rinpharma 2025. Highly recommended if you deal with tabular data and need validation or beautiful summary HTML tables: youtu.be/abvgK9VU7z0 #RStats #python #DataValidation

  20. Just finished watching @rich_i 's great workshop about hist {pointblank} R package / python module, presented at @rinpharma 2025. Highly recommended if you deal with tabular data and need validation or beautiful summary HTML tables: youtu.be/abvgK9VU7z0 #RStats #python #DataValidation

  21. Just finished watching @rich_i 's great workshop about hist {pointblank} R package / python module, presented at @rinpharma 2025. Highly recommended if you deal with tabular data and need validation or beautiful summary HTML tables: youtu.be/abvgK9VU7z0 #RStats #python #DataValidation

  22. Khi làm dự án nhỏ tổng hợp dữ liệu từ API, mình học được:
    - Đường dẫn thành công thì dễ, mọi thứ khác thì không
    - Những giả định nhỏ về phản hồi API gây ra hầu hết sự cố
    - Kiểm tra dữ liệu quan trọng hơn hiệu năng lúc bắt đầu
    Dữ liệu thực tế khác xa tutorial!

    Bạn từng làm dự án liên quan dữ liệu, điều gì khiến bạn bất ngờ?
    #sideproject #apidevelopment #datavalidation #lessonslearned #lậptrình #dựánphụ #xửlýdữliệu

    reddit.com/r/SideProject/comme

  23. Kochava fixes the MMM data problem marketers didn't know they had: Measurement company releases data validation tool addressing broken spend tracking, naming inconsistencies, and revenue gaps that derail marketing mix modeling. ppc.land/kochava-fixes-the-mmm #Marketing #DataAnalytics #MarketingMixModeling #DataValidation #Measurement

  24. Kochava fixes the MMM data problem marketers didn't know they had: Measurement company releases data validation tool addressing broken spend tracking, naming inconsistencies, and revenue gaps that derail marketing mix modeling. ppc.land/kochava-fixes-the-mmm #Marketing #DataAnalytics #MarketingMixModeling #DataValidation #Measurement

  25. Kochava fixes the MMM data problem marketers didn't know they had: Measurement company releases data validation tool addressing broken spend tracking, naming inconsistencies, and revenue gaps that derail marketing mix modeling. ppc.land/kochava-fixes-the-mmm #Marketing #DataAnalytics #MarketingMixModeling #DataValidation #Measurement

  26. Kochava fixes the MMM data problem marketers didn't know they had: Measurement company releases data validation tool addressing broken spend tracking, naming inconsistencies, and revenue gaps that derail marketing mix modeling. ppc.land/kochava-fixes-the-mmm #Marketing #DataAnalytics #MarketingMixModeling #DataValidation #Measurement

  27. Kochava fixes the MMM data problem marketers didn't know they had: Measurement company releases data validation tool addressing broken spend tracking, naming inconsistencies, and revenue gaps that derail marketing mix modeling. ppc.land/kochava-fixes-the-mmm #Marketing #DataAnalytics #MarketingMixModeling #DataValidation #Measurement

  28. Xây dựng nền tảng phân tích dữ liệu sản xuất để giải quyết vấn đề "dữ liệu xấu"!
    Nó bao gồm:
    - Xác thực schema và kiểu dữ liệu thời gian thực
    - Phát hiện và làm sạch PII
    - Kiểm tra quy tắc kinh doanh
    - Cách ly tự động sự kiện xấu
    #PhânTíchDữLiệu #DữLiệu #Analytics #DataValidation #OSS #MởNguồn #CongNghe #Technology #DataScience

    reddit.com/r/SideProject/comme

  29. Tự động hóa kiểm tra dữ liệu hàng loạt giúp tiết kiệm thời gian và giảm rủi ro. Bài viết chia sẻ thách thức và kinh nghiệm tích hợp API để xác thực email, số điện thoại, IP và user-agents. Hiệu quả ROI cao so với kiểm tra thủ công. #DataValidation #TựĐộngHóa #KiểmTraDữLiệu #XửLýDữLiệu #Automation

    reddit.com/r/programming/comme

  30. 🚀 A practical data efficiency tip for software developers & tech leaders:

    ✅ Treat your data like you treat your code!

    Instead of waiting for data problems to surface in production — or worse, in your ML models or analytics — you can catch them earlier by integrating data checks into your development workflow.

    Here’s how:
    💡 Add data validation tests to your CI/CD pipeline — just like unit tests for code.
    💡 Define and enforce data contracts (expected schemas & rules) between teams or systems.
    💡 Run automated change impact analysis when modifying data pipelines to see what breaks before deploying.

    By shifting these checks left — into your CI/CD pipeline — you avoid expensive downstream failures, reduce debugging time, and deliver more reliable ML and analytics outcomes.

    Start small: pick one critical dataset or pipeline and add basic schema validation to your PR checks. You’ll thank yourself later.

    💻📊 #SoftwareDevelopment #DataValidation #CI/CD #TechLeadership #ML #Analytics

  31. 🚀 A practical data efficiency tip for software developers & tech leaders:

    ✅ Treat your data like you treat your code!

    Instead of waiting for data problems to surface in production — or worse, in your ML models or analytics — you can catch them earlier by integrating data checks into your development workflow.

    Here’s how:
    💡 Add data validation tests to your CI/CD pipeline — just like unit tests for code.
    💡 Define and enforce data contracts (expected schemas & rules) between teams or systems.
    💡 Run automated change impact analysis when modifying data pipelines to see what breaks before deploying.

    By shifting these checks left — into your CI/CD pipeline — you avoid expensive downstream failures, reduce debugging time, and deliver more reliable ML and analytics outcomes.

    Start small: pick one critical dataset or pipeline and add basic schema validation to your PR checks. You’ll thank yourself later.

    💻📊 #SoftwareDevelopment #DataValidation #CI/CD #TechLeadership #ML #Analytics

  32. 🚀 A practical data efficiency tip for software developers & tech leaders:

    ✅ Treat your data like you treat your code!

    Instead of waiting for data problems to surface in production — or worse, in your ML models or analytics — you can catch them earlier by integrating data checks into your development workflow.

    Here’s how:
    💡 Add data validation tests to your CI/CD pipeline — just like unit tests for code.
    💡 Define and enforce data contracts (expected schemas & rules) between teams or systems.
    💡 Run automated change impact analysis when modifying data pipelines to see what breaks before deploying.

    By shifting these checks left — into your CI/CD pipeline — you avoid expensive downstream failures, reduce debugging time, and deliver more reliable ML and analytics outcomes.

    Start small: pick one critical dataset or pipeline and add basic schema validation to your PR checks. You’ll thank yourself later.

    💻📊 /CD

  33. Oh, the irony! Oracle, the self-proclaimed fortress of cybersecurity, gets "allegedly" breached, and their customers are left validating the stolen data. 🚀 Meanwhile, the article demands cookies and JavaScript like a petulant toddler demanding snacks. 🍪🤦‍♂️
    bleepingcomputer.com/news/secu #OracleBreached #CybersecurityIrony #DataValidation #CookiesJavaScript #HackerNews #ngated

  34. Oh, the irony! Oracle, the self-proclaimed fortress of cybersecurity, gets "allegedly" breached, and their customers are left validating the stolen data. 🚀 Meanwhile, the article demands cookies and JavaScript like a petulant toddler demanding snacks. 🍪🤦‍♂️
    bleepingcomputer.com/news/secu #OracleBreached #CybersecurityIrony #DataValidation #CookiesJavaScript #HackerNews #ngated

  35. Oh, the irony! Oracle, the self-proclaimed fortress of cybersecurity, gets "allegedly" breached, and their customers are left validating the stolen data. 🚀 Meanwhile, the article demands cookies and JavaScript like a petulant toddler demanding snacks. 🍪🤦‍♂️
    bleepingcomputer.com/news/secu #OracleBreached #CybersecurityIrony #DataValidation #CookiesJavaScript #HackerNews #ngated

  36. Oh, the irony! Oracle, the self-proclaimed fortress of cybersecurity, gets "allegedly" breached, and their customers are left validating the stolen data. 🚀 Meanwhile, the article demands cookies and JavaScript like a petulant toddler demanding snacks. 🍪🤦‍♂️
    bleepingcomputer.com/news/secu #OracleBreached #CybersecurityIrony #DataValidation #CookiesJavaScript #HackerNews #ngated

  37. Transform Your Family History: Introducing gedcom2wiki for Effortless Genealogy Sharing

    Tired of clunky family tree websites? Meet gedcom2wiki, a Python tool that converts your GEDCOM files into a user-friendly, Wikipedia-style family tree, complete with data validation. Say goodbye to o...

    news.lavx.hu/article/transform

    #news #tech #Genealogy #GEDCOM #DataValidation

  38. Transform Your Family History: Introducing gedcom2wiki for Effortless Genealogy Sharing

    Tired of clunky family tree websites? Meet gedcom2wiki, a Python tool that converts your GEDCOM files into a user-friendly, Wikipedia-style family tree, complete with data validation. Say goodbye to o...

    news.lavx.hu/article/transform

    #news #tech #Genealogy #GEDCOM #DataValidation

  39. Transform Your Family History: Introducing gedcom2wiki for Effortless Genealogy Sharing

    Tired of clunky family tree websites? Meet gedcom2wiki, a Python tool that converts your GEDCOM files into a user-friendly, Wikipedia-style family tree, complete with data validation. Say goodbye to o...

    news.lavx.hu/article/transform

    #news #tech #Genealogy #GEDCOM #DataValidation

  40. Transform Your Family History: Introducing gedcom2wiki for Effortless Genealogy Sharing

    Tired of clunky family tree websites? Meet gedcom2wiki, a Python tool that converts your GEDCOM files into a user-friendly, Wikipedia-style family tree, complete with data validation. Say goodbye to o...

    news.lavx.hu/article/transform

    #news #tech #Genealogy #GEDCOM #DataValidation

  41. Well, that's a convenient pick up point for your pacel if you're sailing to the UK, I guess?
    #DataValidation #GoogleMaps

  42. Well, that's a convenient pick up point for your pacel if you're sailing to the UK, I guess?
    #DataValidation #GoogleMaps

  43. Well, that's a convenient pick up point for your pacel if you're sailing to the UK, I guess?
    #DataValidation #GoogleMaps

  44. Well, that's a convenient pick up point for your pacel if you're sailing to the UK, I guess?
    #DataValidation #GoogleMaps

  45. Discover how to implement advanced data validation using Marshmallow in Flask applications. This comprehensive guide covers essential techniques to ensure data integrity, improve security, and build more robust web applications. #DataValidation #Flask

    teguhteja.id/advanced-data-val

  46. 👀 ODE helps you find errors in your datasets and correct them in no time – a process called #datavalidation in industry jargon. It also checks that your dataset has all the necessary information for others to use, guaranteeing, again in technical jargon, data #interoperability.

  47. 👀 ODE helps you find errors in your datasets and correct them in no time – a process called #datavalidation in industry jargon. It also checks that your dataset has all the necessary information for others to use, guaranteeing, again in technical jargon, data #interoperability.

  48. 💭 #DFIR Thoughts
    It is a generalized misunderstanding that the column names and descriptions of a report generated by a digital forensics tool are the last word on what an artifact is or what it means. This erroneous assumption is so pervasive that it can be seen even within our organizations and labs.

    Using a tool that has been blessed as tested and verified does no mean that proper interpretation of the data and/or report is not needed anymore. It also does not absolve the expert from doing their own testing when an artifact is of key importance to a case. It definitely requires that managers stop outsourcing their responsibility to the validation team and really take into account the expertise of the examiners under their care. Even more importantly it should underscore how the best report is not the one that is more favorable to the theory of the case but the one that reflects the data accurately.

    Tool reports are not the data. The data is the data. Validate everything that matters.

    Tools can:
    🔵 Parse data incompletely.
    🔵 Parse data completely but present in a way that could be misinterpreted (which is what happens when new data has to fit in a predefined tool schema that does not provide for a way to indicate possible nuance.)
    🔵 Wholly miss relevant data.
    🔵 Present the data correctly in a way that is easy to understand even to non-experts.
    🔵 Be erroneous.

    The tool has been wrong in the past and it will be again in the future. Does that mean tools are invalidated or useless? By all means, NO! Tool output is not the end of an examination but the start. Tool makers (I am one BTW) strive to make true sense of the data but at the end of the day "it is not the tool that does the exam but the examiner", the person behind the keyboard (thanks to DFIR Training (Brett Shavers) for the quote.)

    If you want to delve more into the topic check out SANS Digital Forensics and Incident Response paper titled Six Steps to Mobile Validation here: sans.org/blog/six-steps-to-suc

    #DigitalForensics #MobileForensics #DataValidation #YouAreTheTool

  49. Data Manipulation Initial Planning Is A Crucial Aspect Of Any Project, & It's One Of My Favourite Parts!

    I still prefer to do this phase 'old school', with a large piece of (portable) paper, pencil, and eraser, revisiting and adjusting as needed, often the next day as it has percolated overnight...
    During this phase, I list constraints, data validation needs, design a broad framework, and determine interactions while trying to future-proof as much as possible. I bring in my requirements and questions from my initial JIRA ticket(s) - and then use these to develop and evolve business rules, along with a process diagram construction.
    From there, it's all on to SQL and manual testing in PostgreSQL + PostGIS and finally prototype app construction - for the devs to then take and make it work fast and well!

  50. 🚀 Exciting news! Pydantic 2.4.0 is here!

    ⚡ Huge performance improvements, new features, and a lot of fixes. See the full list of changes here github.com/pydantic/pydantic/r

    ✨ New features include: Base64Url types, optional number to str coercion, `field_name` and data access in all validators, string validation support, experimental plugins support.

    ⬆ Upgrade today for smoother data validation!

    #Python #Pydantic #DataValidation #OpenSource