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

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

🧵 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 #

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

🚀 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

I built a tool to find problems hiding in my training data.

LabelLens analyzes labeled text classification datasets for duplicates, mislabels, and class imbalance. Ran it on my own 26K sample dataset — found 5,664 exact duplicates I had no idea about.

Try it: https://huggingface.co/spaces/mikenoe/label-lens

Blog post: https://mikenoe.com/posts/i-built-a-tool-to-find-the-problems-in-my-training-data/

#MachineLearning #DataQuality #NLP #OpenSource

Données de mauvaise qualité = décisions erronées, temps perdu, réputation en danger. Solutions : validation, documentation, formation. Pour les décideurs : interrogez la tech !

#DataQuality #DataEngineering #DecisionMaking #DataGovernance #RiskManagement

https://www.linkedin.com/posts/gabriel-chandesris_dataquality-dataengineering-decisionmaking-activity-7434990709910261760-nkc3