Big data analytics
81% of the IT decision-makers surveyed said their organization uses machine data analytics for technology operations management, and 60% cited using it for security.
51% said their company depends on machine data analytics for big data projects, and the same percentage cited internet of things (IoT) uses.
Faster time to value: 24%, Increased revenue: 23%, Improved productivity: 18%, Faster time to resolve incidents: 17%, Faster time to market: 11%
Logistics: 52%, Industrial IoT: 49%, Predictive maintenance: 39%, Smart buildings: 36%, Smart meters: 32%
86% of the IT decision-makers surveyed said that at least 11 people interact with their machine analytics technology at least once a week, and 15% said more than 50 people do.
IT operations and DevOps staff: 78%, Data analysts: 68%, Data scientists: 49%, Business analysts: 38%, Business users: 36%
39% of the IT decision-makers surveyed said their machine data analytics technology is open source, 36% said it’s proprietary and 25% said it’s a mixture of both.
Of those using at least some form of open-source tech for machine data analytics, 52% said they do so due to the low upfront costs, and 49% cited low ongoing costs as a factor.
Of those using some form of open-source tech for machine data analytics, 42% said they do so because the IT staff prefers open source, and 23% said “it was the best tool for the job.”
Demands on infrastructure resources: 36%, Demands on staff: 33%, Difficulties in scaling: 33%, Slow production of analytics and reports take too long to design: 32%, Excessive costs: 31%