by Rick Skriletz –
Due to the constant state of change IT has seen for 30 years, we in IT have become inured to the dramatic change in our profession.
First came the transition from mainframe to client-server applications. This was followed by mega-applications replacing individual specialized ones, then, in succession, transitions to the internet, mobile, and cloud-based applications as well as dealing with the outsourcing of IT staff.
What that means today is that IT is inundated with technology promises called Hype. So, the question is “what’s next” to come out of Hype as the next dramatic change for IT? That answer is becoming clear and it has two key components: Cloud and Big Data.
The advantages of Cloud are clear. The majority of CIOs I have spoken with over the past two years want to get out of running data centers. Additionally, business users are adopting SaaS solutions for their agility, use of OpEx rather than CapEx expenditures, and lack of need for IT support.
But what about Big Data?
In 2015, Gartner took Big Data off of their Hype Cycle because they no longer considered it “an emerging technology.” Yet, the explosion of high-tech companies offering Big Data, artificial intelligence, Internet of Things, cognitive computing, and other advanced technologies makes the impact of Big Data seem more anticipated than real. That is not the case.
Big Data is fundamentally changing the IT data landscape, data management technologies and approaches used by IT, analytic technologies that support the business, and IT’s potential for delivering value to the business. It is doing this by being: usable in real time; consistent across all applications and platforms; technically straightforward to reduce IT complexity; and able to provide instant delivery of business applications.
All of these, like the major changes that preceded them, will bring significant change to IT. Consider what it means to be:
- usable in real time – an on-demand world requires applications, data, and analytics ready to run at the moment needed;
- consistent across all applications and platforms – ready to run means that no time is available to reconcile or correct differences in rules or data;
- technically straightforward to reduce IT complexity – CIO magazine for a decade has pointed to technology complexity as a hidden and, so far, insurmountable burden on the effectiveness of IT, so IT solutions that take advantage of Big Data, artificial intelligence, Internet of Things, cognitive computing, and other advanced technologies need to reduce, if not eliminate, this complexity;
- able to provide instant delivery of business applications – computing hardware and software continue to expand into the realm of what people do; if technology can drive cars, it can produce business applications.
New Skills and Capabilities
Just as the internet, mobile, and other past technology changes required IT to develop new skills and capabilities, so do these changes. For example:
- IT data landscape – current data landscapes (the physical data stores and technologies that hold business data) make up the complexity that engulfs IT today, so any migration to data lakes and cloud should be done in a way that reduces IT complexity;
- data management technologies and approaches used by IT – new technical skills and data management processes will be required because new technologies cause changes to work that needs to be done and to the way in which it is done;
- analytic technologies that support the business – advanced analytic capabilities from machine learning, artificial intelligence, and cognitive computing require non-traditional data types, non-relational data structures, and advanced technical capabilities, changing responsibilities for data management and analytics;
- IT’s potential for delivering value to the business – just as business users adopt SaaS solutions for the agility they provide, the ability to use OpEx rather than CapEx expenditures, and their lack of need of IT support, IT’s value proposition to the business must provide the same value as it delivers usable, consistent, straightforward, and instantly delivered data and analytics.
Cloud and Big Data offers CIOs and IT executives a choice: implement these technologies so they add to the complexity of the data landscape or use them as a means to set IT on a new, more productive path to delivering business value.
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