For over 20 years Alan Radding has provided technology writing, analysis, ghostwriting, and blog/online content for a variety of publications, websites, major research and consulting firms, and technology giants like IBM, HP, and EMC. We recently checked in with him about expansions to IBM’s z System and what companies should be doing to stay up to date with innovations in Big Data. Here’s what he had to say:
What technology news or innovations are you most excited about right now?
Internet of Things, Blockchain, open source technology and the continuing growth of cloud computing.
What issues related to Big Data do you think more organizations should be paying attention to?
Near real-time predicative analytics, cognitive computing and automation.
What are the most interesting expansions to IBM’s z Systems you’re seeing?
Linux, Hadoop, support for IoT and Blockchain, support for open technology through open industry consortia like OpenStack, Open Power and the Open Mainframe Project and consortia being formed around Blockchain and IoT.
How would you like to see z System’s footprint expand?
IBM should extend the z further into cognitive computing and bring its latest breakthroughs to storage, such as PCM, to products that work with the z. It also needs to stimulate Open Mainframe Project growth and activity much as it did with OpenPower as well as continue to push OpenStack and openness wherever it has potential.
How should enterprise organizations using z System today be strategizing for the future when it comes to leveraging data and real-time analytics?
They need to immediately add Linux in a serious way to their z environment and begin to participate in the various open consortia where applicable. They need to figure out how they can benefit from IoT and what IoT could do to mainframe resource consumption. They also need to figure out where and how they might benefit from Blockchain, which is essentially a highly secure distributed log file that is only minimally related to electronic money like bitcoins. If they don’t get oriented to the open consortia world they risk being left behind and eventually stranded.
How is z System being used for real-time analytics?
With Hadoop running on the z, it is possible to do near real time analytics on the z (notice near real time; in truth nothing is actually real time, there always is some latency). This is possible because most of the data already resides on the z platform so your analytics there will have the least possible latency and generate the least overhead, avoiding delays and extra expense.
What is the demand for real-time analytics today? What types of industries are asking for it?
The demand is growing, starting in the expected industries: financial services, health sciences/pharmaceuticals. With IoT real-time analytics will attract manufacturing, transportation, logistics, oil & gas exploration. Real-time analytics will be particularly appealing with IoT in retail and financial services for security, allowing a company to identify the bad guys before they leave the cash register or bank teller window.
What do you think the future looks like for how enterprise organizations manage data? What will be their go-to tools?
If companies do not move real time analytics they will get left behind. Same with predictive analytics; both real-time and predictive need to run in tandem. IoT, Blockchain, mobile, and OLTP have the potential to generate so much data so fast that their people using anything but automated smart systems with minimal latency will be unable to recognize important information and act on it quickly enough.
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