AI can accelerate the work of identifying duplicates, detecting inconsistencies and supporting data-quality processes. But useful AI depends on trustworthy information. Golden records provide a stronger foundation for analytics, automation and AI-driven decisions.

#AI #DataQuality #MasterData

A digital asset record should reflect the physical asset in the field. Physical verification and asset walk-downs help connect what systems say with what actually exists, supporting more trustworthy asset information and lifecycle management.

#AssetManagement #DataQuality #DigitalTransformation

Before improving enterprise data, organizations need to understand its current condition. A data health assessment can reveal gaps in completeness, consistency, duplication and structure—providing a practical starting point for improvement.

#DataQuality #DataManagement #DataGovernance

Procurement performance depends partly on the quality of the information behind every purchase. Standardized materials, consistent classifications and trusted supplier-related data can create greater visibility across the procurement process.

#Procurement #DataQuality #SupplyChain

Inventory optimization starts with knowing exactly what exists, where it is used and how it is described. Clean, standardized material data helps reduce duplication, improve visibility and support more informed inventory decisions.

#InventoryManagement #DataQuality #SupplyChain

🚀 #FabConEurope starts today!

Data quality often comes up late: when a report looks odd or a pipeline fails. So we built a new HEDDA.IO Workload for #MicrosoftFabric that covers the steps before that.

📍Booth 21, CCIB Barcelona
Bring your toughest #DataQuality questions.

Asset handover is more than transferring equipment and documents. It is the point where accurate asset information becomes operational knowledge—supporting maintenance, planning, compliance and reliable decisions from day one.

#AssetManagement #DataQuality #DigitalTransformation

New arXiv paper reframes data quality for AI-driven systems, interviewing 16 practitioners across 9 organizations and surfacing six themes, including traceability shifts and circularity when models assess their own data.

#DataQuality #AIEthics #SoftwareEngineering
https://arxiv.org/abs/2609.31191

A report that has never shown a problem has not been tested. It has been lucky. Ask what would have to happen for your main number to go red, and see if anyone can answer.

#DataQuality #Operations

A failed AI pilot usually gets blamed on the model. Check the data: hand-picked demo extract, no data owner, over-broad access, sources that disagree. www.convective.com/blog/signs-... #DataQuality #AIStrategy

Data quality improves when it is visible and measurable. Scorecards and monitoring provide a practical way to identify issues, track quality and focus improvement efforts on the areas that need attention.

#DataQuality #DataGovernance #DataManagement

Preventive maintenance relies on useful information. Capturing structured equipment and maintenance data helps organizations build a stronger information foundation for planning, monitoring and asset performance.

#Maintenance #AssetManagement #DataQuality

End-to-end supply chain visibility depends on connected and reliable information. Bringing together demand, inventory, orders and transportation data creates a clearer view of what is happening across the supply chain.

#SupplyChain #DataQuality #SupplyChainManagement

SAP transformation is also a data transformation. Strong data readiness—through validation, preparation and governance—helps create a more reliable foundation for SAP RISE & GROW initiatives.

#SAP #SAPRISE #DataQuality #DataManagement

Asset information should remain valuable throughout the asset lifecycle—from acquisition and commissioning through maintenance and eventual disposal. Consistent data supports better decisions at every stage.

#AssetManagement #DataQuality #DigitalTransformation

Good data governance requires more than policies. Clear ownership, defined responsibilities and accountable stakeholders create the structure needed to maintain reliable enterprise information.

#DataGovernance #DataManagement #DataQuality