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Digitalisation hinges on data core transformation

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Businesses are at a turning point using modern technology while still maintaining the legacy of traditional IT.
This hybrid model requires CIOs to evaluate the key components that make up the foundation of their organisation’s technology core and create an approach that provides flexibility to integrate emerging technology trends like the cloud, artificial intelligence and cybersecurity.
Speaking ahead of his track at the Gartner Symposium/ITxpo in Cape Town in September, David Willis, vice-president and distinguished analyst at Gartner, explains the transformation of the enterprise technology core and the emerging technology trends driving it.

The technology core has been previously described as three interdependent components that enable a company to join the digital era: renovated postmodern ERP, service-oriented architecture and advanced analytics solutions. Have these components evolved, and is there an opportunity for the definition of the technology core to evolve?
The technology core is the foundation that builds your organization’s capabilities for the digital era. In the last year, we’ve seen a major migration toward the cloud, which indicates that the definition and role of the technology core will continue to evolve. Specifically, cloud has made a significant impact to four major pillars that now make up the foundation of the enterprise technology core:
* Infrastructure;
* Applications;
* Data and analytics; and
* Integration platforms.
The cloud has gone much more mainstream in enterprises than what skeptics had anticipated. Because of this, it has also disrupted how businesses embrace the cloud as a platform for digital business. With the migration to the cloud, business organizations have more options and a different level of scale that allows them to uniquely position their capabilities to be a more efficient, streamlined digital business. Overall, there is more trust in the cloud.

What other elements have disrupted the technology core?
Data and analytics will be much more transformational over the next few years. It’s one of the most critical pillars. Insight is essential to the digital business transformation. And as we move into a world of the Internet of Things (IoT), algorithms and data will have even more power, not just in the virtual world but in the physical world, too.

How has the emergence of artificial intelligence (AI) and smart machine learning altered the foundation of the technology core?
First, AI and machine learning is different in practice than in what we learned in school or in popular media. Today’s AI systems aren’t human brains in digital form. They are systems that learn on their own and produce responses that the original designer did not intend. So in fact, they may do things that humans aren’t good at. And it’s here now, not something for the next decade.
To give you a real, practical example, virtual personal assistants and chat bots are appealing to businesses with major call centre operations. Organisations have started to adopt these digital assistants to provide better customer service, increase their call volumes and control costs. They’ll be taking on more complex tasks, taking inputs from more sources at a higher rate than any team can. So they will soon address issues with talent shortages.

Are there any other trends on the rise that you anticipate will transform the technology core in the next five years?
Look at what is happening with the customer experience. Advancing and improving augmented reality, virtual reality, multiscreen interaction, and other immersive and ambient experiences are right on the horizon. We will also start to see many versions of devices first targeted at consumers being brought into use inside of business.
Things like head-mounted displays and wearables will provide better information in the moment, improve worker efficiency, and — here’s a big one — improve the safety of workers.
We are at an interesting intersection between a new type of synthetic intelligence, blending data and analytics with machine learning. It’s critical to transform the technology core in order to prepare for those innovations.