Data collection

Data collection involves the systematic collection, storage and analysis of data in order to make informed decisions. In industrial companies, data collection plays a crucial role in the areas of quality management (QM), quality assurance (QA), production, logistics and IT.

Challenges

• Data quality: Inaccurate or incomplete data can lead to incorrect analyses and decisions.
• Data integration: Merging data from different sources and systems can be complex and error-prone.
• Data security: Protecting sensitive data from unauthorized access and data loss is a constant challenge.
• Data accessibility: Data must be easily accessible and understandable for the relevant stakeholders.

Solution approaches

• Digital tools: The use of digital applications facilitates the collection and management of data.
• Automated systems: Automated data collection reduces manual errors and improves data quality.
• Integrated platforms: The use of integrated systems enables the seamless consolidation and analysis of data from different sources.
• Training: Employees should be trained in the use of data collection tools to ensure data quality and guarantee data security.

Advantages

Optimizations through digital tools, automated systems, integrated platforms and training improve data quality, reduce errors and increase efficiency. High-quality data improves decision-making, increases transparency and optimizes business processes.

 

Further links:

https://www.testify.io/plasser-australia-digitalisiert-fertigungsdokumentation-mit-testify/