Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Data analytics is increasingly becoming recognized as a valuable set of tools and techniques for improving performance in the manufacturing enterprise. Hover, data analytics requires data and a lack of useful and usable data has become an impediment to research in data analytics. ,  describe issues that would help aid data availability including data quality, reliability, efficiency, and formats specific to data analytics in manufacturing. To encourage data availability,  present recommendations and requirements to guide future data contributions.  also describe the need for data for challenge problems in data analytics. A better understanding of these needs, recommendations, and requirements may improve the ability of researchers and other practitioners to improve research and more rapidly deploy data analytics in manufacturing.
['Don Libes', 'Seung-Jun Shin', 'Jungyub Woo']
I am writing a research paper on a idea Considerations and recommendations for data availability for data analytics for manufacturing
[{"from": "human", "value": "I am writing a research paper on a idea Considerations and recommendations for data availability for data analytics for manufacturing"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Data analytics is increasingly becoming recognized as a valuable set of tools and techniques for improving performance in the manufacturing enterprise. Hover, data analytics requires data and a lack of useful and usable data has become an impediment to research in data analytics. ,  describe issues that would help aid data availability including data quality, reliability, efficiency, and formats specific to data analytics in manufacturing. To encourage data availability,  present recommendations and requirements to guide future data contributions.  also describe the need for data for challenge problems in data analytics. A better understanding of these needs, recommendations, and requirements may improve the ability of researchers and other practitioners to improve research and more rapidly deploy data analytics in manufacturing."}]