Machine Data Analytics Aids Big Data and IoT Efforts- Valutrics

Businesses must boost operational efficiencies enterprisewide if they want to keep up with rapid market and technology shifts. And many are investing in machine data analytics to do so, according to a recent survey from Logtrust and 451 Research. The resulting report, “The Need for Speed: Machine Data Analytics in 2016-17,” indicates that organizations are deploying the latest in machine data analytics to benefit big data and internet of things (IoT) efforts, as well as overall IT operations and cyber-security. Subsequently, they’re increasing revenue and productivity, with quicker incident resolutions and time to market for products and services. To continue to make progress, IT will need to overcome obstacles in infrastructure and staffing demand, as well as difficulties in scaling, to manage data ahead of the pace of business and technology changes, instead of falling behind. “It’s been shown time and again that in all sorts of areas, the value of data erodes dramatically as it ages,” according to the report. “In other words, the faster you can run some analytics on data and subsequently respond to the findings, the greater the chance of having achieved something that adds business value: the take-up of specific offers, a reduction in customer churn or basket abandonment, or resolving a situation in which a company may have been left with customer ill-will and poor reviews, for example. … In fact, [big data is] of far less importance than the notion of ‘fast data.’ How quickly can data be ingested, processed, analyzed, visualized and acted upon? For more and more companies, this is one of their biggest challenges if they are to remain competitive.” An estimated 200 IT decision-makers took part in the research.

Protected Production

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.

Data Driven

51% said their company depends on machine data analytics for big data projects, and the same percentage cited internet of things (IoT) uses.

Benefits of Machine Data Analytics

Faster time to value: 24%, Increased revenue: 23%, Improved productivity: 18%, Faster time to resolve incidents: 17%, Faster time to market: 11%

IoT-Related Machine Data Analytics Areas

Logistics: 52%, Industrial IoT: 49%, Predictive maintenance: 39%, Smart buildings: 36%, Smart meters: 32%

Routine Function

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.

Employees Most Likely to Interact With Machine Analytics

IT operations and DevOps staff: 78%, Data analysts: 68%, Data scientists: 49%, Business analysts: 38%, Business users: 36%

Preferred Paths

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.

Cost Considerations

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.

Open Minded

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.”

Challenges of Machine Data Analytics Tech

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%