by Angela Guess
David Adamson recently wrote in Datanami, “Today’s IT teams have enough on their hands managing data-storage infrastructures, without having to worry about issues with an array or latency problems that no one seems to be able to understand or solve. But what if the customer support around these issues could be managed by a team that is systematically ingesting and cleanly organizing a huge variety of customer data to pinpoint the exact issue? This is where data scientists come in. Data scientists today are dissecting and analyzing trillions of data points to identify and solve the problems that keep IT teams up at night. As data-center infrastructures continue to become more complex, data scientists are treating the ever-increasing workloads weighing down IT teams.”
Adamson goes on, “They demonstrate the power of the infrastructure to allow the answering of many arbitrary, unpremeditated questions about a customer’s environment with relative ease. Following we explore the ways in which data analytics is quickly becoming a critical component of IT — and how data scientists can empower IT teams with greater visibility into their entire infrastructure. Providing effective and efficient technical support for data-storage infrastructure is a hard problem. In large part, this difficulty stems from the complexity of the IT stack. Complex interactions between complex products create a wide variety of technical problems ranging from the subtle (misconfigurations, product conflicts, software bugs, resource imbalances) to the mundane (loose cables). To diagnose problems in this environment, an equally wide variety of information is necessary — and because of this, a big data solution is required.”
photo credit: Flickr/ Stinging Eyes