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How to Deploy Advanced Analytics in the Enterprise? Start with IT

How to Evaluate Predictive Analytics for Your Business Of all the ways in which advanced analytics and machine intelligence can impact the enterprise business model, perhaps none is more crucial than its effect on IT itself. As infrastructure becomes more distributed and data loads become more complex, IT must become more adaptive, even to the […]

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Arthur Cole
Arthur Cole
Oct 26, 2016
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How to Evaluate Predictive Analytics for Your Business

Of all the ways in which advanced analytics and machine intelligence can impact the enterprise business model, perhaps none is more crucial than its effect on IT itself.

As infrastructure becomes more distributed and data loads become more complex, IT must become more adaptive, even to the point where it exceeds a technician’s ability to collect operating data, figure out what it all means and implement the required changes. So before organizations turn Big Data loose on functions like sales, marketing and compliance, it makes sense to implement it on the infrastructure and operational layers of the data environment itself.

This can be done in numerous ways. Power management firm Eaton recently launched the PredictPulse Insight platform that uses a cloud-based analytics engine to track power distribution throughout the data center to predict failures and optimize efficiency. The system ties into the PredictPulse remote monitoring service to produce a more predictive, proactive model of energy management. Users are provided with real-time data over an online dashboard that details alarm settings, performance metrics, service history and a host of other points, all of which can be accessed by either a traditional web portal or a mobile app.

Analytics will also play a key role in the deployment of converged and hyperconverged infrastructure. Lenovo and Nimble Storage recently teamed up to improve resource deployment and other tasks related to infrastructure management by integrating the XClarity infrastructure management stack into the Nimble InfoSight analytics and automation platform. The aim is to produce a self-healing computer-storage-networking infrastructure that handles day-to-day management tasks so technicians can focus on strategic objectives. The system will be deployed on the ThinkAgile CX series modular platform that is set to enter the channel by the end of the month.

Meanwhile, Zenoss and a company called SaltStack are linking up their respective analytics and intelligent orchestration software to enable autonomic provisioning of software-defined infrastructure. The solution will leverage event-driven automation tools and advanced monitoring and data collection to provide on-demand deployment of AWS instances, as well as automated configuration management and performance optimization to support advanced DevOps workflows and efficient data asset utilization. Key capabilities include autonomous capacity scaling, intelligent system remediation and continuous security compliance monitoring.

Analytics can also be applied to targeted IT functions, such as backup and recovery. HPE recently unveiled a new Adaptive B&R Suite that uses operational and file analytics to automate and streamline data protection. The platform combines existing tools like the HPE Storage Optimizer, Data Protector and Backup Navigator, and harnesses them under a data optimization, analytics and performance engine that boosts insight into the operational characteristics of increasingly distributed and virtualized data environments. In this way, operators gain improved insight into risk factors surrounding ongoing deployment and operational trends and can take steps to minimize them before performance is affected on the user level. IT also assumes much of the hands-on tasks surrounding daily backup tasks and streamlines recovery test procedures. (Disclosure: I provide content services for HPE)

The increased use of analytics is almost a given as the data center becomes more automated. Before long, IT infrastructure will have tremendous capacity to not only evaluate its own operating conditions but project how they will change in the coming weeks or months and then take steps to ensure that changes are carried out seamlessly and with only rudimentary oversight.

And once IT has mastered the use of intelligent, analytics-driven operation, it will be in a better position to apply this knowledge to the business side of the enterprise.

Arthur Cole writes about infrastructure for IT Business Edge. Cole has been covering the high-tech media and computing industries for more than 20 years, having served as editor of TV Technology, Video Technology News, Internet News and Multimedia Weekly. His contributions have appeared in Communications Today and Enterprise Networking Planet and as web content for numerous high-tech clients like TwinStrata and Carpathia. Follow Art on Twitter @acole602.

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