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Big Data trends you need to know in 2022
Artificial Intelligence

Big Data trends you need to know in 2022 

Big Data trends you need to know in 2022- Big Data is one of the pillars of our increasingly digital future. This prognosis is so contrasted in the current context that it is practically indisputable, except for some type of major social or planetary catastrophe. The simple reason is this: as our lives, economic activity, personal habits, and social fabric become increasingly digital, they produce vast and growing amounts of data about our activity. This data is always stored somewhere, be it by corporations or government agencies, and if it is there, different interests will find different uses for this tidal wave of information. Some of these uses have the potential to be downright dangerous, especially in terms of personal privacy and corporate/government abuse.

First, what is Big Data?

To better understand Big Data trends, we must first define this area in a way that separates it from ordinary digital data sets. In short, Big Data is information that contains an immense variety of sources and origins, arriving in exponentially increasing volumes and cannot be categorized or analyzed by traditional processing software, much less by human analysts. In other words, Big Data involves processing data from various sources, at high speed, and with a wide variety of data, including unstructured data as well. Velocity, volume, and variety are commonly considered the “three Vs” that define Big Data as different from normal volumes of data flow.

cloud migration

Cloud migration has been an integral part of Big Data and data analytics for years. In fact, it is one of the essential components of these interconnected technologies. After all, how can we collect and analyze vast amounts of data if it’s not directly accessible to the kinds of data analysis software and AI systems that are capable of handling it? Being able to access and use Big Data requires migration to the cloud from its most localized sources. Cloud computing and Big Data have been hand in hand for years, and their collaboration will continue to expand into 2022 and beyond.

Personalized Advertising and Marketing

One of the primary uses for much of the volumes of business, consumer, and other data collected today is advertising and content personalization. This especially applies to consumer data on personal habits and interests collected on a large scale. The first parts of using this data involved directing it to individuals, companies or organizations specifically for their interests. In DataCentric we have several examples of this, for example, from XcampaignWe can send an email to a million people, personalizing not only general questions such as their gender or name, but completely individualized content based on their interests and past browsing. One of the next steps, which already refined in 2022, to also add a predictive aspect to ads or marketing campaigns.

In other words, we focus not only on targeting based on current interests or needs, but also on targeting marketing towards needs and interests that we can predict from these. In the increasingly fierce competition for eyeballs and ears on today’s Internet, predictive marketing and quality advertising will become immensely valuable to marketers.

internet of things

The Internet of Things (IoT) will see tremendous growth in the very near future and some of this will expand further this year. The reason is simple: Internet of Things devices, or classically non-computing devices that now come with computerized data collection and processing capabilities, are becoming more and more common and their data production will be of interest 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 are fully functional only if connected to broadband networks. As dangerous as this trend is from a privacy perspective,

predictive improvements

Outside of predictive marketing and advertising use cases, Big Data analytics will continue to refined to work to improve the capabilities of predicting the future, as complicated as that is. These will apply to financial markets, political crises, public health situations, and many other contexts that are relevant to both business and government programs.

NGOs also expected to benefit from these predictive refinement trends that will become more and more acute in 2022. In fact, one of the main areas of future development of Big Data analytics will lie in improving its predictive capacity so that it can xused by advance, rather than reactively. Predictive improvements through Big Data will be especially important for practical problems like traffic management, healthcare, and forecasting economic trends. But let’s understand each other, in most cases we are not looking for reliable predictions, there will always be a margin of error, what we are looking for is to reduce it as much as possible. In that sense, sinceDataCentric’s analytical team generates many scores that allow us to improve the effectiveness of a segmentation or prescreen potential defaulters.

Natural Language Processing (NLP)

As the volume of content produced and ingested in large data sets increasingly includes human-produced text, video, and audio content, the AI ​​technologies being developed for natural language processing will become extremely important. NLP AI will need to be able to read and then interpret human audiovisual input more effectively and accurately, and the volume of this will grow tremendously in the coming years as more people create individual content through social media sources. .

Filtering and qualification of data

Big Data also means managing a lot of noise that needs to sorted out to get useful nuggets of actionable information. The eternal challenge of data-mining. Being able to do this requires better data filtering and qualification. The importance of these things will lie in sorting through genuine trends of misinformation, misdirection, and a general deluge of data that might not relevant to any specific use case, but still needs to be vetted in some way to gauge its usefulness. AI programs and algorithms will further improve in 2022 for the sake of better data filtering and qualification. Organizations that can best create or use these tools will have an advantage over those that cannot. In this sense,


Big data tools and storage infrastructure remain expensive enough to be impractical for players working on anything less than corporate or government budgets. This will change, however, and could create a new wave of OSINT (open source intelligence) advancements that are truly outside the realm of what government or large enterprise organizations are planning. Recent cases of OSINT being used and leaked on a smaller scale (without using Big Data levels of analysis and processing) include non-governmental tracking initiatives of Russian military movements in the invasion of Ukraine and investigative reporting initiatives of organizations like Bellingcat. These will expand and eventually make use of Big Data analytics,

Disease and social research

In the wake of the immensely costly and deadly COVID-19 pandemic that has gripped the world since early 2020, the use of data for medical predictions and mass research has fiercely debated in many political circles. Big data analytics will play an absolutely important role in promoting this type of research so that pandemics can better understood and managed. One obstacle to medical Big Data is access to medical records in many jurisdictions.


Big data collected on massive and distributed cloud servers managed by many organizations with varying levels of security quality will be extremely vulnerable to growing cybersecurity issues affecting all uses of digital data. Just as hackers are leaking more and more information from conventional corporate databases or simply holding those databases hostage with ransomware, they could potentially do the same with truly huge Big Data sets, possibly with very costly consequences for privacy, business and government policy.

privacy initiatives

A large proportion of Big Data sources comes directly from individuals connected to the Internet, and another significant part comes from the databases of organizations that collect individual information from their users. All these sources of information make these people (including all of us) increasingly vulnerable to having their most personal and private information exposed to many others. That is the existing problem. An even scarier situation will emerge as the treasure troves of Big Data better mined, analyzed, and filtered in predictive patterns. The information used for these data enhancements will exploited in ways that could cause enormous privacy impairments for billions of people. In DataCentric we have as a principle, the “compliance by design”. That is, to articulate from the beginning any new product or data solution with wickers that comply with current regulations and transparency in the use of personal data.

Big Data in problem solving

If you or your organization also want to make use of the top big data analytics trends of 2022 for various reasons, you don’t necessarily need the technical and hardware capacity to do it on your own. Data Centric specializes in data management, enrichment, analysis, and insight activation into business and marketing actions. We can help you.

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