Industry 4.0 has transformed manufacturing, reshaping the competitive landscape and powering innovation. By leveraging disruptive technologies such as AI and 3D printing, factories increase productivity while quickly adapting to customer demands. At the same time, the changing landscape underscores the importance of data quality and security in manufacturing. For example, a smart factory might use 3D printing to create complex customized products on demand. Additionally, smart sensors constantly monitor for minute changes in machine health, optimizing maintenance and minimizing downtime. These improved tools and processes both require and generate huge amounts of data that must be carefully managed and protected.
To keep pace in a competitive environment, manufacturers must harness the power of data to improve processes and decision making. However, rapid digital transformation, evolving market demands, and heightened customer expectations introduce unique challenges to manufacturing data governance. Utilizing data governance best practices can help. Unique Manufacturing Data Governance Challenges Like nearly all industries, the manufacturing industry runs on data. Unprecedented quantities of information offer tantalizing opportunities to upgrade processes, spark innovation and improve the customer experience. But with those opportunities come some challenges. Important information hidden in mountains of data – Manufacturing generates huge amounts of data from a