Data Center, Meet Cognitive Computing
As the number of devices in the world grows exponentially, so, too, does the data they generate. Fortune estimates that data flows into the world at a rate of 50,000 gigabytes per second. With more data entering the data center, it’s more challenging for companies to make sense of it.
Cognitive computing can help businesses disentangle their data and unleash its value. In a cognitive data center, data that comes in is directed to the appropriate place to receive the right services. Initially, policies are set by administrators, but the cognitive system makes adjustments as it learns.
A cognitive data center also leverages software-defined networks (SDNs) and network function virtualization (NFV) to allocate resources more efficiently. Thus, the data center becomes far more powerful, scaling beyond the limits of human administration.
Bringing Order to Big Data Chaos
Data is only worthwhile when it leads to relevant and accurate insights, notes Elementum Founder and CEO Nader Mikhail in Fortune. Right now, businesses are so overwhelmed by data that they’re either gaining false insights from analyzing too little data (or the wrong) data, or they’re getting trapped in analysis paralysis.
“Our business data is overwhelming and distracting us,” Mikhail writes, “throwing up barriers to productive decision-making. It’s virtually impossible to collect only the data you really need, and therefore, you are much more likely to be using data that you shouldn’t.”
Machine learning uses a looping algorithm that takes data inputs and creates a model as an output. This model can then be used to make predictions based on the data that comes in. A cognitive system acts on its prediction, monitors the results and incorporates the feedback before taking its next action. Automated cognitive systems can perform loop algorithms an indefinite number of times extraordinarily quickly.
Throughout the machine learning process, cognitive computing helps to identify the data businesses should be using. Less time is wasted crunching data that won’t yield useful insights. Data is also better protected because cognitive systems keep data more secure. According to MIT, machine learning can reduce cyberattacks by 85 percent, Digital Trends reports.
Superior Service Management
Cognitive computing also helps organizations realize SDN and NFV’s full potential by supervising a pool of network resources and allocating them in more efficient ways. Thus, data centers can run more workloads on existing hardware, improve performance and consume less power. Data is also stored and organized more intelligently by a cognitive data management system, enabling different file and object systems to share data efficiently.
Mac Devine, IBM Fellow, VP and CTO of Strategic Customer Success, Watson Cloud Division, also envisions cognitive computing as a tool to enable more data processing and analysis at the edge. Instead of having data centers, he envisions enterprises having centers of data operating on a distributed basis, Tech Republic reports.
Data collected by the Internet of Things devices, for example, can be processed and analyzed at the edge, with only necessary information and workloads coming into the central data center. This speedy decision-making helps to eliminate false positives, recognize relevant signals and prevent downtime, hardware damage and injuries.
Cognitive Computing Means Fewer Blind Spots
As they seek value in unstructured data, some companies are amassing data in giant data lakes hoping that it will someday yield insights. Other companies segment data from their back-end systems, reserving it only for select users. Devine says cognitive solutions eliminate subjectivity, making relevant data accessible to everyone. Insights won’t get lost in the bottomless data lake, and they’re not siloed where only certain users and systems can benefit.
Devine acknowledges that IT may feel uncomfortable with increasingly independent and automated data center management. At the same time, with so many endpoints generating data, human decision-making simply can’t keep up. By effectively allocating data center services and analyzing data to produce truly relevant insights, cognitive systems can operate more efficient data centers and unleash greater human ingenuity.