The Data Factory: Put the data to work | SPONSORED
Industrial organizations are facing a new challenge as they generate more data than ever before. With the rise of the Internet of Things (IoT) and Industry 4.0, these organizations are looking to institute AI and analytic applications to transform their operations and give them a competitive advantage. However, implementing these technologies is not as simple as it seems. One major hurdle that industrial organizations must overcome is the chasm in understanding between IT and OT teams.
DataOps is a new concept for industrial organizations, and it is essential for bridging this divide. As an operations leader, you understand the value of automation and operations management systems. However, you may struggle with the IT concepts and terminology that are more well-known in commercial businesses such as banking, ad-tech, and insurance. However, you do appreciate how a factory works and how well-designed production processes execute. This is where Industrial DataOps comes in.
Industrial DataOps is a lot like a factory production line in the way it automates, upgrades, improves, and assembles another valuable raw material, data. By understanding how a manufacturing plant is optimized, you can better understand how to apply the principles of DataOps to your organization. This will help bridge the divide between the plant manager and the central IT manager, allowing for a better understanding of professional data management and driving sustainable digital transformation.
In conclusion, industrial organizations are facing a new challenge as they generate more data than ever before. DataOps is a critical concept for bridging the divide between IT and OT teams and driving sustainable digital transformation. By understanding how a manufacturing plant is optimized, operations leaders can better understand the principles of DataOps and apply them to their organizations. More about Who owns the Machine Generated Data in IoT
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