Big Data Begins: IT Hero Rising
Let’s get the harsh facts out there first – IT’s in trouble, deep trouble.
Let’s get the harsh facts out there first – IT’s in trouble, deep trouble. It has become way too reactionary. By IT I mean ‘traditional’ IT, the time honored ‘old school’ way of doing things. The pace of tech adoption is accelerating. By rights this should be a terrific opportunity for technologists and IT teams. In reality, old school IT has been shocked and awed by the consumerization of IT.
The paradox, is that while technology has never been more essential to business success – or more deeply ingrained in businesses, the IT function itself is under siege. Frequently bypassed, over stretched and buffeted by powerful consumer driven trends like mobile, cloud and social – the IT profession is often (sometimes unfairly) viewed as a roadblock that’s in the way of progress.
However, there is hope for the Chief Information Officer and the IT team. My advice is to stop reacting to consumerization of IT and get in front of it: don’t let your business partner get ahead of you on tech exploitation options. Big Data is one area where IT has the opportunity to be the hero, not the laggard. Moving forward it’s what IT does with Big Data that will define how it is perceived within the Enterprise. Below I’ll outline some practical examples of how Big Data – driven by IT – can help businesses succeed.
Get Scientific to Drive High value – Enterprises need to realize that so early in the evolution of big data they have to give data science a chance to take route. It’s essential to link all of these data sources. Big data is the biggest thing that IT needs to think about because it will cross over so many areas of the business. If you look at IT now, CA owns IT management for many large companies with a vast amount of spending. Our customers have routers, networks, servers and hard disks – all busy working away – and all the while our monitors and probing are constantly collecting data about fault levels to help optimize their performance. Another example of IT getting to grips with growing volumes of data is one of CA’s apps – it collects multiple data streams into a repository – crunching down waves of information into something digestible.
The Physical Challenge of Big Data involves managing the various layers of IT infrastructure – There are three different data repositories. All these different domains have their own spinning disc. We need to make all these discs connect to one fabric that allows big data to comprehensively process data into actionable insight. This is so important because this is where the magic is.
Killing Data Keeps Enterprises Safe – Customers ask us to capture data, then show them a real time view – we end up throwing out any data that’s extraneous. A typical big data monitoring app throws out 97 percent of data collected within minutes. That’s a lot of data pruning but it allows the focus to shift to contextual and actionable insights. By bringing all of this critical data together we can actually have a real time overview that tells us for sure if the customers’ business is being attacked. Their application is linked to the right security products and is tracking things like login attempts. From an IT perspective there are some near term adjacencies to the things we currently do. The biggest value for big data has yet to be cracked. The obvious next step is interrelate all data sources and much better predictability, analysis, forecasting by looking back.
Big Data can also ensure greater levels of supply resilience across the business. Let’s consider our energy sources for IT. Previously there was no ability in place to predict when a device would fail. But via SCADA devices, we can now collect and monitor the flow of energy. Through big data we now know something will happen before it happens and most likely know what those needs are. Typical symptoms indicating likely failure are things like fan speed and the temperature of a device. This not only indicates when something will have a fault but also which type of fault it will have. This can be invaluable insight when maintaining the physical integrity of a business, especially in low latency, mission critical environments.
Securing Ecommerce – Another example is building a fraud prevention network. CA can provide back end credit card validation system which caters for the majority of e-commerce activity. Those who are trying to threaten financial network with fraudulent purchases are doing it across a number of different banks. By spreading their efforts they are trying to stay under the radar and keep people from noticing their efforts. CA uses big data as a central hub – so we get the opportunity to see what these criminals are up to. Crossed domains and companies are allowing us to see things across a broader scale.
The current phenomenon around combining mobility and big data is beginning to evolve into the Internet of Things (IoT). Through IoT machines will be able to communicate and collaborate in new and exciting ways. Soon we will not be thinking of these things separately, they are already largely co-dependent on each other. Currently big data is behind mobility in terms of on the ground adoption, this is because mobility became incredibly inexpensive and successful very quickly. As a result, mobile initiatives generated new contextual and personalized data streams that businesses could see and wanted to act on via big data approaches. The two trends are mutually reinforcing.
So to conclude, if you’re starting on your own big data initiative you must consider the following:
Big data is a golden opportunity to resolve some of the long standing tensions between IT and the broader business. Ultimately, we all need to be going on this exciting journey together.