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Five IT trends to watch in 2020

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By Alberto Pan, Chief Technical Officer, Denodo 

Edge Computing will emerge as the key to device management 

Next year, devices are set to become smarter than ever before. The use of them is will also increase to new levels. Already, through the collection and analysis of data, these devices – whether they be voice assistants or smart thermostats – are able to learn about our preferences and adjust accordingly. 

But, the volume of data they collect is expected to exceed record levels in 2020. The more devices we use, the harder it becomes to collect all data into a central repository, analyse it and then push the resulting recommendations back to the device. Next year, businesses will need to adopt technologies that execute the compute function on these devices, or on the ‘edge’ of these devices, rather than doing it centrally. This will enable devices to learn and adjust in real-time.  

The use of data fabrics will increase 

In 2020, the search for an effective integration platform to access and utilise data and deal with issues like data security and siloed information will continue. But an increased amount of organisations will look towards using a data fabric to overcome these data challenges.  

By combining historical and real-time data sets across multiple data silos, a data fabric offers a single, secure and consistent data management framework. It reduces data delivery and helps to support the automation of data preparation and integration as well as enabling organisations to focus more on machine learning and artificial intelligence.  

Legacy to Cloud: hybrid, multi-location architecture will become the norm 

In 2020, as the cloud initiative progresses with more and more data migrating to the cloud, the center-of-gravity will shift. The balance will tip towards platforms where the data is spread across both cloud and on-premises data sources.  

Similarly, integration of the data will transition to a multi-location architecture. Unlike traditional data integration technologies, data virtualisation was designed from the beginning to provide data location transparency, data abstraction, and integrated security across multiple locations, which makes it a perfect fit for these scenarios. Therefore, it will take an increasingly important role in hybrid architectures next year. 

Voice technologies will infiltrate the office 

Voice assistants have established themselves as common place in our personal lives. But 2020 will see an increasing amount of businesses turning to them to improve and personalise the customer experience.  

This is because, advances in AI-driven technology and natural language processing are enabling voice interactions to be translated into data. This data can be structured so that conversations can be analysed for insights. 

Next year, organisations will likely begin to embrace conversational analytics to improve their chatbots and voice applications. This will ultimately result in better data-driven decisions and improved business performance. 

Selling information to third-parties using the Data-as-a-Service approach will become a growing source of revenue for big companies 

The effective use of enterprise data for strategic decision making has become a key priority for all big companies in the last few years. As a consequence, companies have created high quality datasets and a sophisticated technology architecture to manage them and expose them to consumers.  Companies have also invested heavily in automating their business processes for greater efficiency.   

In the new year, since many big companies will now own high-value, unique data and services, the next logical step is reusing this infrastructure in order to offer them to third-parties. For instance, we are already seeing telecommunications companies selling customers geolocation data for a variety of purposes. This trend will be significantly accentuated during 2020 in all major industries. 

From the investment standpoint, this will involve higher demand for the technologies involved in creating and exposing data as a service, like GraphQL, Data Virtualization and/or API management tools.

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