Big Data Analytics in Industrial Intelligence

Big data analytics is a complex procedure for discovering hidden patterns, trends in industries and also for customer preferences. The Fourth Industrial revolution is the blending of real world with the virtual world. This digital revolution takes the trump card of big data analytics and artificial intelligence to bring up the automated learning system. Industries apply big data to polish their marketing campaigns and use this technology in machine learning projects to edify machines and for predictive modelling. Also, big data helps industries to give rise to valuable insights. Industries such as airline, healthcare, banking, government, and retail contain large amounts of data, so they rely on the big data analytics technology for their ease of use.

Frequently used techniques in industrial big data analytics are highly distributed industrial data ingestion, industrial big data repository, large scale industrial data management, industrial data analytics, and industrial data governance. These techniques are used to enhance information retention in education industry, to prepare a law enforcement for a crime taking over in a long period of time, and to audit the large sets of data in banking industry. Yet, these operations in the industries cannot be undertaken without the help of key tools such as Hadoop to store data, MongoDB for data sets, Talend for data integration, Cassandra for chunks of data, and Kafka for fault tolerant storage.

Although industrial intelligence implements big data into its process successfully, it also faces a challenge of security attacks, confusion in tool selection and lack of proper understanding of massive data. In future these challenges can be resolved by selecting the apt tool with the help of experts and can access control implementation with the help of cyber security tools. In the final analysis big data is going to be very big in the industrial intelligence which cannot be handled by human society. So, every individual should be ready to make use of this tremendous technology in every aspect of life.

Topics of interest include, but are not limited to the following:

• Developments in machine learning and big data for supply chain management in manufacturing Industries
• Future directions of big data and artificial intelligence in automated production
• The power of embedded sensors in the manufacturing value chain using big data analytics
• Overview of role of big data in the media and entertainment industry
• Role of big data in the improvement of government process performance, enabling better experience and improvement in transaction process
• Analytics: the real-world use of big data in manufacturing industry
• Big data security analytics: a weapon against increasing cyber security attacks

Submissions Deadline: March 31, 2023

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