A digital universe can be described simply as all the data that humans have created, copied, and made accessible digitally.
And according to IT tech leaders who attended a recent enterprise tech convention in Cebu, Philippines, the digital universe will be 20 trillion gigabytes large by 2020.
As reported, the enterprise tech solution providers are finding ways to manage that crucial area by shaping solutions.
Data management is something that should not be left unattended by client businesses, whether big or small.
Learning to manage data efficiently and rolling out solutions to intelligently process and manage all the information coming from all sides are key pillars to digital transformation.
It was reiterated that enterprises should adopt better data management practices and solutions because the data explosion is far from over and is expected to continuously grow exponentially.
It was discussed that smart cities is one avenue from which data will be coming from. These are cities that use an array of connected sensors within the city for various beneficial purposes.
The smart city process involves a whole lot of interconnectivity at the many interaction points between people and objects within the city. In addition, it will need a lot of sensors.
Light posts, for instance, will be able to detect when a person is in the area and automatically increase the brightness of its lamp. It will then turn it down when no persons are detected.
A system like this will generate significant savings for the city but will generate more data.
One way of managing the influx of data from smart cities is by standardisation. Using aggregation instead of the siloed approach can manage data better.
The siloed approach is a fragmented approach that does not lead to information sharing, thereby leading to duplication in technologies and investment.
Furthermore, processes are not streamlined in a siloed environment, which would require extra steps and time that could have been saved.
Aggregation, on the other hand, is a system where all the information comes to one place, where all the various devices and sensors can be integrated into a network that works seamlessly with one another.
With the growth of the digital universe, the pot of gold, which hackers can dip their fingers in, also does. The more data becomes available, the more data can be stolen.
The average cost of a breach, worldwide, now costs US$ 4 million for large businesses.
These large consumer-facing businesses have a large database of users hence, more data to steal and monetise for the hackers.
Ransomware has become a big attack trend recently. It works similarly to kidnapping, wherein a person will only be returned according to the terms of the attacker.
The only difference is that it is valuable and crucial data that is being held in captivity.
In the coming years, managing ransomware attacks and other types of hacking will only get more complex because of a number of reasons.
One is the interconnected internet-of-things (IOT). This encompasses that every object that is able to connect to a network and to one another will be generating and collecting more data.
Because of this, there are more entry points for the attackers.
Secondly, the speed at which attacks are detected needs to ideally be as fast as possible.
However, according to a regional solutions architect, the average number of days before an attack is detected is 99 days.
It is not fast enough. Businesses should invest in better, faster detection measures because there are more chances of limiting the potential damage if the attack is detected faster.
Moreover, it will allow for a faster deployment of the appropriate counter-response.
It’s a tug-of-war though, said the expert, as hackers find a way to be sneakier as cybersecurity firms sharpen their noses.
Artificial intelligence (AI) is one way that cybersecurity firms are able to sharpen their detection skills, just as many other companies in other verticals are attempting to speed up data processing with AI.
As people generate and put more data online, which could be targeted by hackers, AI and machine learning are relying on a ton of data in order to learn how to spot certain behaviour signals.
The expert demonstrated this through their AI-powered malware detection system for email, which is able to identify malicious email that seems to have been sent by a real person within a company.
Studying the writing style of a person, the AI is able to spot the tiny differences in writing style between the legitimate email and the fake email, eventually flagging the fake one.
Aside from AI, there are other technologies that can be used for data management today. A chief technologist showed blockchain and its potential.
Blockchain, because of its immutability, can hold much more authentic data, and this frees people from the extra process of determining the data’s trustworthiness.
Instead of having to swim in a sea of data, a blockchain can be set up to track products. For example, diamonds.
The blockchain will be able to tell and record where each diamond comes from, potentially decreasing the chance that a person will buy a “blood diamond” from conflict areas.
Despite all of these fancy-sounding technologies helping people manage data, the executives agree that the human being’s role in all this will not be completely replaced.
AI will not be replacing the human being. Instead, it will just do things faster.
A healthy mix of tech and human agency appear to be the general strategy in containing the data explosion that the information age has brought.
