Data is the commodity that fuels modern-day manufacturing.
The uptick in industrial innovation, from real time inventory management to remote machine monitoring, is inherently centered around data.
As manufacturers gather impressive amounts of information from different sources and mine it for powerful insights into equipment performance, product quality, or supply chain visibility, a rigorous data integration environment is an underlying necessity.
A constant stream of timely information is presumably the engine of manufacturing growth. Admittedly, immense swaths of data that capture machine-level information are poised to optimize field operations, prevent unscheduled downtime, and yield superior demand forecasts.
But the mere amount of data is not necessarily an indicator of intelligent manufacturing processes—a high level of data usability is.
Any given dataset is deemed valuable only if it’s useful, manageable, and actionable. When the attention is diverted away from these rigorous standards, low-quality information may lead to faulty assumptions and, as a result, bring manufacturing operations to an abrupt halt.
Amid rising data quality-related concerns, manufacturers process and share a daily tangle of information across multiple systems or applications. There is, however, a fairly robust link that can unify all this continuously-acquired data to help professionals extract more value from it.
That link is called data integration.
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