Data Center Automation Market Detailed Analysis by 2020
The global data center automation market size was valued at $2,483 million in 2015, and is projected to reach $8,619 million by 2022, growing at a CAGR of 19.6% from 2016 to 2022. The IT & telecom segment was the highest contributor in 2015, accounting for around 23% of the global market.
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A data center is a facility that consists of a network of computers and storage systems. It is used to process, organize, store, and distribute large amounts of data for a business or an organization. Data center automation offers faster and enhanced productivity, operational reliability, and consistency to its users, which results in its increased demand in various industry verticals.
The report features a competitive scenario of the data center automation industry and provides comprehensive analysis of key growth strategies adopted by major players. Key players profiled in the study are VMware, Inc., BMC Software, Cisco Systems, Inc., IBM Corp., Hewlett Packard Enterprise, Microsoft Corp., Puppet, Citrix Systems, Inc., ServiceNow, Inc., and Chef Software, Inc.
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Based on the geography, the data center automation market is segmented into North America, Europe, Asia-Pacific, and LAMEA. North America was the highest revenue contributor in 2015, accounting for around ~60% share of the market size. However, Asia-Pacific is projected to grow at the highest CAGR of 25.3%, owing to the adoption of data center automation techniques to achieve effective and efficient control over the ongoing processes and operations.
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Manufacturing is expected to grow at the highest CAGR of 22.8% during the forecast period. In the manufacturing industry, large amount of data is generated on the operation and shop floor, which needs to be analyzed to improve the quality, accuracy, and delivery time. By automating the data center, the data can be accessed continuously for performing predictive analysis to identify relationships and patterns among various processes and associated factors to recognize and enhance those factors that have the largest impact on the output.
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