Disruptive Technologies: 2020 technology trends

Data becomes the center of the IT universe

Operational and digital transformation is all in the data: how you collect it, what you do with it, the platforms you have to manage it and how you make it available.

Greater volume, greater detail, greater insights

The ability to decouple data from applications allows organizations to really embrace operational transformation and digital transformation.

Volumes of data collected at the most granular level from IoT devices and digital platforms – effectively any technology system – can now be made available through application programming interfaces for analysis, business insights and developing additional applications.

We're not just collecting more data, we're also collecting more granular data, allowing us to deduce more insights than were ever possible.

With enough datapoints, you can model behaviour and understand patterns – for example, the diet of someone’s biometric twin – and come to more accurate conclusions (the time it would take before a health incident occurs), more quickly, and at a fraction of the cost of modern-day science.

Data is also critical for next-generation technologies: digital twins, spatial computing, artificial intelligence, deep analytics and new applied versions of technology are all dependent on data platforms. The data platform will even enable the next generation of computing architectures, such as serverless computing.

Data lake or data swamp?

Data truly is the center of it all and it’s therefore critical to get the data platform right. Data strategies must consider the architecture for capturing and managing all types of data – structured, semi-structured, unstructured and streaming – and making it accessible through APIs and a data service catalogue so a wide set of stakeholders can use it to create new value.

It is data that allows insights that transcend human observations or interpretation, and exposes truths or realities undetectable in the past. It is data that shows that it's not the fastest cyclist who wins the race, and it is data that changes a public transport company into a provider of consumer presence patterns for the retail industry.

Organizations that don’t build these disciplines around data will find themselves swamped by its scale rather than inspired by its potential.

NTT’s Digital Twin Computing Initiative uses data such as geographical and transport information to create virtual societies that can accurately predict the spread of an infection and help to control a real-world outbreak, in real time.

Applied technology explodes to bridge the digital and physical

Using technology that’s applied with a specific outcome in mind will bring us to some interesting intersections between the physical and digital worlds. Here’s a brief look at what’s to come.

Seamlessly blending a world of realities

Applied technology will not just help us bridge the gap between our physical and digital worlds; it will allow us to blend them seamlessly. Spatial computing will introduce us to a whole realm of realities – virtual, augmented, enhanced, hyper, mixed, authentic – and digital interfaces will expand to include multiple senses: sight, sound, touch, smell. Immersive environments, where the physical and digital blend, will have a pervasive impact on the industry.

It might start as a dual-screen experience – where traditional formats such as high-definition images are complemented by a real-time second screen, using augmented reality to enrich the viewing experience – and evolve to volumetric capture technology, such as NTT’s Kirari!^®, that will bring this to life at scale with holographic telecasting.

Opening new worlds of possibility

Given the growth and granular collection of data at scale, data modeling will evolve to encompass all systems and processes, enabling the exploration of digital twins across multiple research areas. The scale and scope of what is possible are in their infancy. The application of technology is finding its way into areas previously unthinkable – and at a speed that is unforeseen.

NTT and Major League Baseball will collaborate to create an exciting new baseball fan experience using NTT’s Ultra Reality Viewing that’s based on NTT’s Kirari!^®. Audiences will be able to view sports content as if they were watching it live in the stadium.

Programmability and predictive capabilities reshape cybersecurity

A fundamental shift is taking place in cybersecurity as new technologies enable greater predictive capabilities and security at an atomic-unit level.

Blockchain finding its use case

Blockchain is finding its use case beyond just the international settlement areas, and we have seen its adoption extend to all areas of the financial sector, even unexpected ones. As an example, blockchain provides more control over data and can be used as an entirely new approach for managing configuration provenance in IT systems.

With blockchain, agent software can run on every device in a physical or virtual environment so that all devices participate in a distributed ledger. You can then run the hash of the block on the config file to render the hash code of the block, indicating a state of the overall configuration posture. If the hash code changes, it means there’s a change in the config – and suddenly you have an immutable mechanism to detect the change (in real time), trace it through the block, and identify the origin and party responsible for the change. There’s a lot of potential for this technology to have a great impact on cybersecurity, perhaps even to redefine cybersecurity as we know it today.

Programmability and security at an atomic level

As every element of infrastructure and architecture becomes programmable, we can start thinking about security posture as code. If we can put a firewall inside the software of all containers and virtual machines in our architecture, and contain the flow of data between them within software, security vulnerabilities are greatly reduced – there are simply no doors in the wall you can pick the lock for. If you can maintain the dataflow in software, it’s never on a network where it can be hacked, siphoned off or stolen. Some vulnerabilities will still be there but the granularity, contained dataflows and software greatly reduce and improve the vulnerability profile.

In a way, this leverages the brute force of programmability to embed security technology at a granular level and orchestrate the outcome at a scale that was not feasible in the past. This is good news for the industry and we’ll continue to see this capability emerge as programmability evolves and improves.

Predictive power for detection and prevention

Cybersecurity is one of the first IT functions to mature in using large-scale data with machine learning, analytics and artificial intelligence to become more predictive. The more data sets we collect over time, and the richer that data is, the better we can determine and match patterns to both predict and shut down attack vectors. This is a major step – a major and very positive step.

The scale and granularity of measures we can take with programmability and the resulting data that is generated, coupled with machine learning, analytics and predictive artificial intelligence, allow us to combine powerful technologies to curtail security threats more effectively. We’re better able to detect and contain these threats before they manifest, leading to the phenomenon of negative-day attack prevention, as opposed to zero-day prevention.

NTT’s Piper platform, a highly scalable machine learning pipeline, enables us to handle billions of flows hourly – generating over 300 unique statistical features (for example, global geolocation distribution) for each internet host – and track their locations.