Show threadZenn Trends22h ago

📰 Claude Code Agent Teamで実現するAIのためのデータ品質向上プロセス (👍 32)

🇬🇧 Using Claude Code Agent Team to improve data quality with Tier-based system. Automates the bottleneck of upgrading data for AI readiness.
🇰🇷 Claude Code Agent Team으로 Tier 기반 데이터 품질 향상. AI 활용 가능한 데이터로 업그레이드하는 병목을 자동화.

🔗 https://zenn.dev/dely_jp/articles/claude-code-agent-team-design

#ClaudeCode #DataQuality #AI #Zenn

Claude Code Agent Teamで実現するAIのためのデータ品質向上プロセス

Zenn
Show threadZenn Trends1d ago

📰 Claude Code Agent Teamで実現するAIのためのデータ品質向上プロセス (👍 30)

🇬🇧 Using Claude Code Agent Team to automate data quality improvement process. Tier-based quality system for AI-ready data.
🇰🇷 Claude Code Agent Team으로 데이터 품질 향상 프로세스 자동화. AI 활용 가능한 데이터를 위한 티어 기반 품질 시스템.

🔗 https://zenn.dev/dely_jp/articles/claude-code-agent-team-design

#DataQuality #ClaudeCode #AIReady #Zenn

Claude Code Agent Teamで実現するAIのためのデータ品質向上プロセス

Zenn
Julian Schwarzenbach5d ago
If you are interested in #dataquality and #ai, then this free webinar tomorrow may be of interest/ use: https://www.eventbrite.co.uk/e/author-webinar-series-data-quality-in-an-ai-world-with-julian-and-tim-tickets-1981419239283
Author Webinar Series - Data quality in an AI world with Julian and Tim

Join us for a deep dive into data quality as a strategic enabler for AI-driven organisations, with authors Julian Schwarzenbach and Tim King

Eventbrite
Paul Welty6d ago

Executives keep asking "How do we use AI to make better decisions?"

The honest answer: clean your data first. Deduplicate your contacts. Reconcile the three spreadsheets tracking the same metrics with different definitions.

Nobody wants to hear that. So they build dashboards on top of garbage and blame the model when outputs are incoherent.

The intelligence was never the bottleneck.

https://www.paulwelty.com/the-loop-nobody-bothers-to-close/

#AI #DataQuality #FeedbackLoops #Leadership

The loop nobody bothers to close

Most systems observe. Almost none learn. The difference is a feedback loop — and the boring cleanup work that makes it possible.

Paul Welty, PhD
HackerNoonMar 19
Data observability monitors nulls, drift, and freshness, catching pipeline issues before they corrupt dashboards, models, or business decisions. https://hackernoon.com/building-data-observability-monitoring-nulls-drift-freshness-and-business-impact #dataquality
Building Data Observability: Monitoring Nulls, Drift, Freshness and Business Impact | HackerNoon

Data observability monitors nulls, drift, and freshness, catching pipeline issues before they corrupt dashboards, models, or business decisions.

HitechDigital SolutionsMar 18

Improving CRM Data Reliability for Better Business Insights

As customer information evolves, CRM databases require regular attention to stay useful. Incomplete or duplicate records can affect analysis and outreach. A trusted data cleansing company helps maintain structured data that supports clearer decision making across teams.

Know more: https://www.hitechdigital.com/blog/crm-data-cleansing-customer-database

#DataCleansingCompany #CRMDataCleansing #DataQuality #CleanData #DataManagement

HEDDA.IOMar 18

🧵 Poor data quality rarely announces itself loudly.

Are you safe, or can you spot some warning signs in our guide? 👇

https://hedda.io/when-data-turns-against-you-spotting-and-handling-early-signs-of-data-quality-issues/

#DataQuality #DigitalTransformation #DataStrategy #

MoniSa EnterpriseMar 10
#AIData #DataAnnotation #AIML #LLMTraining #DataQuality #ResponsibleAI
sayzardMar 10

Paweł Budzianowski (@pfbudzianowski)

로봇 데이터 수집 확장은 까다롭다는 내용의 안내로, 텔레오퍼레이터마다 조작 방식이 다르고 장비마다 특성이 있어 잘못된 에피소드가 정책 학습에 악영향을 줄 수 있다고 지적합니다. 이를 해결하기 위해 유효한 예시는 유지하면서 노이즈를 걸러내는 품질 필터 개선 기법을 공유한다고 발표한 기술 안내 게시물입니다.

https://x.com/pfbudzianowski/status/2031135588498247922

#robotics #dataquality #dataset #robotlearning

Paweł Budzianowski (@pfbudzianowski) on X

Scaling robot data collection is messy. Every teleoperator moves differently, every rig has quirks, and bad episodes silently poison your policies. We share how we improve quality filters that catch the noise without throwing away good examples.

X (formerly Twitter)
NFDI4CultureMar 6

🚀 Die 8. Ausgabe der Reihe „Workshop Retrodigitalisierung“ findet vom 19.–20.03. im Haus Unter den Linden (Berlin), und unter dem Oberthema „Digitalisierung für die Ewigkeit? – Datenqualität in der Praxis“ statt.

👉 Anmeldungen sind noch bis zum 11.03. möglich: https://pretix.eu/StaatsbibliothekZuBerlin/WS-Retrodigi/

✨ Die @stabi_berlin richtet den Kurs gemeinsam mit @tibhannover, @ZBMED, ZBW – Leibniz-Informationszentrum Wirtschaft und @nfdi4culture aus.

#NFDIrocks #Retrodigitalisierung #Dataquality