This report titled ‘Global Big Data Market in the Manufacturing Sector for 2016-2020‘, provides an in-depth analysis of the market in terms of revenue and emerging trends. To calculate the market size, the report considers the revenue generated from the sales of big data solutions in the manufacturing sector, including software, integrated solutions, and services.
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“APAC will lead the high adoption of the solution during the forecast period, given the increase in the adoption of IoT, ICT, and M2M technologies. Different sectors in China and Japan are using M2M integrated with IoT technology for better communication between machines. Organizations have been slow in adopting big data solutions because of the lack of awareness about integrating big data technologies with the existing systems in manufacturing processes for better management,” said Amrita Choudhury, one of Technavio’s lead industry analysts for enterprise application research.
Some of the other driving forces behind the growth of the global big data market in the manufacturing sector are as follows:
- High demand for effective data access
- Exponential growth in data
- Increased adoption of IoT
High demand for effective data access
Big data solutions provide objective information about enterprise performance. They help enterprises store a large volume of data ranging from data about product portfolios to employee details for future use, etc. Enterprises are keen to use this data to identify patterns and predict opportunities and threats. The need for secure and easy access to data is met by the different functions of big data solutions such as data recovery and retrieval.
Easy accessibility of data is helping organizations achieve their corporate and long-term goals. In addition, the need for improvements in the development of next-generation products and services requires enterprises to use enterprise big data effectively. Additionally, greater emphasis on improving decision-making is driving the increasing demand for effective access to big data.
Exponential growth in data
Enterprise data in the manufacturing sector is generated from a number of sources, including enterprise applications, web-based searches, supply chain and employee details, and cloud-based applications. Any US enterprise with more than 1,000 employees has on average more than 200 terabytes of stored data. It is practically not possible to analyze such large volumes of data manually. Organizations require big data analytics and solutions to keep track of such huge volumes of big data generated to use it effectively. Big data analytics help enterprises optimize their business decisions and innovate new business models, products, and services.
Increased adoption of IoT
IoT uses technologies such as radio-frequency identification, sensors, barcodes, and GPSs. These technologies can be used to monitor and manage physical assets in an organization. For instance, radio-frequency identification–tagged goods are easier to track in the supply chain of manufacturing and retail companies. In addition, radio-frequency identification helps manage and maintain the inventory of an organization. This increases the efficiency of the enterprise and improves business values. With the help of IoT, every device or asset of an organization is interconnected with other assets. With the adoption of this technology, enterprises are expected to witness significant improvements in business processes, with greater control that eventually leads to more effective decision-making in real time.
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