Big data is one of the pillars of our increasingly digital future. This is a prediction so rooted in present day facts that it’s virtually indisputable barring some sort of major social or planetary catastrophe.
The simple reason why is this: As our lives, economic activity, personal habits and social fabric become ever more digitized, they produce immense and growing amounts of precise data points about how they operate. This data is always stored somewhere, either by corporations or government agencies, and if it’s there, different interests will find different uses for it.
Some of these uses have the potential to be downright dangerous, especially in terms of personal privacy and corporate/government abuse. Whichever the case may be for any of them, the following are some of the major trends in big data and data analytics that were going to see expand in 2022 and beyond.
First, What is Big Data?
To understand big data trends better, we first need to define this area in a way that separates it from ordinary digital data sets. Simply put, big data is information that contains an immense variety of sources and themes, which arrive in exponentially growing volumes and can’t be categorized or analyzed by traditional processing software and much less by human analysts.
In other words, big data is varied, high velocity, high volume information from diverse sources –usually digital- that can give its harvesters insights on patterns for whatever the data concerns. Velocity, volume and variety are commonly considered to be the “three V’s” that define big data as different from normal data flow volumes.
Cloud migration has been an integral part of big data and data analytics for years. In fact, it’s one of the essential components of these interlocking technologies. After all, how can we collect and analyze immense amounts of data if they’re not directly accessible to the kinds of data analytics software and AI systems that are uniquely capable of handling them. Being able to access and use big data requires cloud migration from its more localized sources. This is already an ever-present trend of big data and its analytics, but it will continue to expand in 2022 and beyond.
Personalized Advertising and Marketing
One of the major uses for much of today’s collected business, consumer and other data volumes is advertising and marketing. This applies especially to consumer data about personal habits and interests collected on a mass scale. The earlier parts of using this data involved targeting it to individuals, business or organizations in ways that were specific to their interests. This is still expanding.
However, one of its next steps, already being refined in 2022, is to also add a predictive aspect to ads or marketing campaigns. In other words, we focus not just on targeting based on current interests or needs, but also aiming marketing towards needs and interests we can predict from these. In the increasingly ferocious competition for eyeballs and ears on today’s internet, quality predictive marketing and advertising will become immensely valuable to sellers.
Internet of Things
The internet of things will see enormous growth in the very near future and part of this will expand further in this very year. The reason why is simple: Internet of Things devices, or classically non-computing devices that now come with computer processing and data harvesting capacity are becoming ever more common and their data production will be interesting to many parties.
Examples of IoT devices include washing machines, car parts, kitchen appliances, household tools and commercial machinery of all kinds. Many of these already contain internal computers and work fully only if connected to broadband networks. As dangerous as this trend is from a privacy perspective, it’s also inevitably becoming ever more interesting for the growing volume of highly personalized information it creates.
Aside from predictive marketing and advertising use cases, big data analytics will continue to be refined towards working for better predictive capabilities in general. These will be applied to financial markets, political crises, public health situations and many other contexts that are relevant to both business and government programs.
NGOs will also hopefully benefit from these predictive refinement trends that were going to see sharpen incrementally more in 2022. One of the major areas of future big data analytics development will in fact lie in enhancing its predictive capacity so that it can be used in advance, instead of reactively. Predictive improvements through big data will be especially important for practical problems such as traffic management, healthcare and economic trend forecasting.
Natural Language Processing
As the volume of content produced and vacuumed into big data sets includes ever more text, video and audio content produced by individual people, the AI technologies being developed for natural language processing will be extremely important. NLP AI will need to be able to read and then interpret human audiovisual inputs more effectively and accurately, and the volume of these will grow immensely in the coming years as more people create individual content through social media sources.
Data filtering and qualification
Big data also means big noise that has to be sorted through for useful nuggets of actionable information. Being able to do this requires improved data filtering and qualification. The importance of these things will lie in sorting genuine trends from misinformation, misdirection and a general outpouring of data that might not be relevant to any specific use case, but which needs to be examined somehow in order to gauge its usefulness.
AI programs and algorithms will improve further in 2022 for the sake of improving data filtration and qualification. Organizations that can create or use these tools better will have an edge over those that can’t.
Big data tools and storage infrastructure are still expensive enough to not be practical for actors working with anything less than corporate or government-level budgets. This however will change and could create a new wave of OSINT (open source intelligence) breakthroughs that are truly outside the realm of what government or big business organizations plan for.
Recent cases of OSINT being used and filtered on a smaller scale (not using big data levels of analytics and processing) include the non-governmental tracking initiatives of Russian military movements in the Ukraine invasion and investigative reporting initiatives by organizations like Bellingcat. These will expand, and eventually make use of big data analytics, maybe not in 2022, but not too far into the future.
Disease and Social Research
In the wake of the immensely costly and deadly COVID-19 pandemic that gripped the world since early 2020, the use of data for medical predictions and mass research has been ferociously debated in many policy circles. Big data analytics will absolutely play a part in furthering this kind of research so that the current pandemic can be better understood on a global scale and future pandemics handled better.
One obstacle to medical big data is access to medical records across numerous jurisdictions. We’ll see how this conflict of interests plays out in this year and the near future.
Big data collected in massive and distributed cloud servers run by many organizations with variable levels of security quality will be extremely vulnerable to the growing cybersecurity problems that plague all digital data uses today. Just as hackers are increasingly leaking information from conventional company databases or simply holding such databases hostage with ransomware, they’ll potentially be able to do the same to truly huge big data sets, possibly with very costly consequences for privacy, business and government policy.
A vast proportion of big data sources comes directly from individuals connected to the internet, and another major part of it comes from the databases of organizations that collect individual information from their users. All of these information sources make these individuals (including all of us) increasingly vulnerable to having their most personal, private information exposed to many others. That’s the existing problem.
An even more terrifying situation will emerge as big data troves are better mined, analyzed and filtered into predictive patterns. The information used for these data improvements will be exploited in ways that could cause enormous privacy deteriorations for billions of people.
Navigating Your Own Big Data Needs
If you or your organization also wants to make use of the major big data anlytics trends of 2022 for any number of reasons, you don’t necessarily need the technical and hardware capacity to do this on your own. Data Centric specializes in data management, analytics and filtration of quality information from noise. We can help you.