New Survey and Customer Data Detail How Data Sciences and Machine Learning Can Predict and Prevent Application Downtime and Close the App-Data Gap
SAN JOSE, CA--(Marketwired - Apr 27, 2016) - Nimble Storage (
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The report surveyed nearly 3,000 IT professionals and business application users based in the U.S., Germany, U.K., Australia, Singapore and Southeast Asia. Nearly two-thirds of all respondents and 76 percent of U.S. respondents reported that the speed of applications they use significantly impacts their ability to perform their best in the workplace. IT professionals, however, don't appear to be aware of the magnitude of the problems residing within their own companies, allowing the small delays from the app-data gap to add up to big headaches. While more than 40 percent of business users say they avoid using some software applications at work because they run too slowly, only 18 percent of IT professionals think their users are either unsatisfied or very unsatisfied with the way software systems work at their companies. A corresponding report, "Can Machine Learning Prevent Application Downtime?" analyzes data collected by Nimble Storage and points to the most pertinent hurdles impacting the speed at which companies access the data that powers applications.
Mind the Gap: How Application Delays Affect Company Performance
Key survey findings:
Millennials Experience the Effects of the App-Data Gap Most
Key Regional Findings
"It's no mystery why business users expect access to data to be immediate and continuous. The conundrum facing IT decision makers is how to predict and prevent performance bottlenecks before users perceive a slowdown in responsiveness," said Suresh Vasudevan, CEO, Nimble Storage. "The performance bottleneck between the data and the application, which we call the 'app-data gap', negatively impacts employee work time and ultimately impairs business performance. We believe that by bypassing reactive approaches for root cause analysis that typically take days or weeks, IT departments can harness data sciences and machine learning to predict and prevent barriers to data velocity while fully empowering employees to achieve their best."
Can Machine Learning Prevent Application Downtime?
Today's IT infrastructure is full of complexity. A major app-data gap can disrupt data delivery, degrade worker productivity, create customer dissatisfaction and damage a company's overall speed of business and reputation. While it's easy and commonplace to point to data storage as the primary culprit for the app-data gap, the factors leading to application slowdowns come from a range of issues across the infrastructure stack.
According to a Nimble Labs Research Report -- which analyzed more than 12,000 cases documenting examples of app-data gap related issues across the Nimble install base of more than 7,500 customers -- 54 percent of all issues have nothing to do with storage. The majority of issues arise from challenges with configuration (28 percent), interoperability (11 percent), non-storage best practices impacting performance (8 percent) and host, compute or VM-related issues (7 percent). Of the 46 percent of storage issues detected, hardware and software problems, software update assistance and performance setbacks are most common.
These findings debunk the IT professionals' first instinct that storage infrastructure is the primary cause of application performance issues. This presumption leads IT professionals to implement fast flash-based storage technologies to accelerate performance, but flash alone does not address the 54 percent of unrelated storage issues. To close the app-data gap, Nimble believes IT organizations need to leverage predictive analytics that incorporate both data science and machine learning to optimize the performance and availability of applications. These technologies are designed to help identify poor performance early, minimize or eliminate the effects of an issue, prevent businesses from encountering the same problem as their competitors and continually improve performance and availability for users.
The Nimble Storage Predictive Flash platform combines flash performance with InfoSight predictive analytics to deliver data velocity. InfoSight predicts and prevents issues across the IT application-to-storage stack that can significantly slow data delivery. The Predictive Flash platform enables IT organizations to accelerate all applications running across the IT environment and deliver immediate access to information that is essential for enterprises to maintain a competitive edge.
For more information on Nimble's Predictive Flash platform, please visit www.nimblestorage.com.
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