🔎 Missing names? Dates stored as text? Too many values where you expected one?
SHACL lets you define rules for RDF data and check your graph against them—catching problems before they reach your applications.
@openknowledgegraphs.com
@openknowledgegraphs.com🔎 Missing names? Dates stored as text? Too many values where you expected one?
SHACL lets you define rules for RDF data and check your graph against them—catching problems before they reach your applications.
3 spreadsheet cleanup mistakes: deleting conflicting IDs, turning unknown amounts into zero, and changing raw data without a backup. Keep an audit trail and reconcile totals. Practise with synthetic data: https://payhip.com/b/R0ove #Excel #DataQuality
Excel duplicate check: enter =COUNTIF($A$2:$A$6,A2), then fill down. A result above 1 flags a repeated ID. Compare other fields before deleting—conflicting records need review. Free lesson: https://payhip.com/RemoteSkillsLab/blog/news #Excel #DataQuality
@dbverstehen.bsky.social🧠 Mega-Tipp für Daten-Cleanliness: Mach eine Dublettenprüfung! 👯♀️📊 Sorgt für saubere und präzise Daten. 🚀 Mehr Infos hier: https://www.datenbanken-verstehen.de/lexikon/dublettenpruefung #Datenbank #DataQuality #Dublettenprüfung
@emailcheckpro.bsky.socialEver notice how your bulk processing pipeline bottlenecks when task size hits the limit? Understanding bulk-task capacity is key to building resilient architecture. Check our docs for details: https://emailcheckpro.com/api-docs?utm_source=bsky #DataQuality #API
@numberchecker.bsky.socialIs your CRM data provenance matching your input source, or is it just 'data soup'? Treating bulk list ingestion as an audit of data-origin consistency helps teams maintain better context before import. https://numberchecker.ai/?utm_source=bsky #DataQuality #CRM
@checknumber.bsky.socialAre you treating every 'registered' WhatsApp contact as an individual lead? A registration signal confirms presence on the app, but it doesn't prove if the account is personal or organizational. Use this context to refine your list triage. https://checknumber.ai/?utm_source=bsky #DataQuality #RevOps
@streamflowai.bsky.socialSomebody changes what a field means and every report inherits it silently. A wrong number tends to look wrong. A number whose definition drifted looks completely normal.
@bluesparrow.devCaching an API response isn't the same as making an app offline-friendly. RideReady keeps forecast data locally with Hive, but cached weather must be identified as cached. Correct bytes can still represent outdated reality. Freshness is part of the data model. #DataQuality #Caching
@heddaio.bsky.socialA column gets renamed. A field arrives empty. The pipeline keeps running, the numbers are wrong for a week.
Schema Contracts in the HEDDA.IO Fabric Workload stop your notebook when a table's schema doesn't match.
Read more 👉 hedda.io/heddaio-sche...
@rwale.bsky.socialYour analysis can be perfectly calculated and still be wrong.
Before building charts, check:
• Missing values
• Duplicates
• Inconsistent dates
• Wrong data types
A beautiful dashboard cannot rescue dirty data.
What is your first quality check?
#DataAnalytics #DataQuality
@pixoate.bsky.socialOne misread digit can change a product code or an order quantity. This guide covers OCR errors that look plausible, the ones a spreadsheet adds on import and how to review them.
@numdect.bsky.socialStop using Global Carrier Lookup as a subscriber-identity tool. It is designed for network-infrastructure diagnostics, not identifying individuals. Use it to understand routing capacity, not to verify who owns a number. https://numdetect.com/?utm_source=bsky #DataQuality #CarrierIntelligence
@ekycpro.bsky.socialIs your API integration handling data errors, or just ignoring them? Treating REST API response codes as a sandbox for data consistency—like mapping specific error states to your intake logic—helps build a more resilient pipeline. https://docs.ekycpro.com/?utm_source=bsky #API #DataQuality
@checknumber.bsky.socialHow do you prioritize your outreach when lead lists are noisy? Using platform-registration signal density can help your RevOps team qualify leads before you commit to deep-dive research. Learn more at https://checknumber.ai/?utm_source=bsky #RevOps #DataQuality
@pixoate.bsky.socialOCR getting numbers wrong? Not every error is a misread. Sometimes the spreadsheet turns a correct code or date into something else on import. Know which one you're fixing.
@pilogian.bsky.socialDuplicated, incomplete and inconsistent information can create hidden costs across an enterprise. Identifying information gaps can help turn data quality from an abstract objective into measurable business value.
