While businesses around the world struggled to stay afloat in 2020, one of the most significant challenges for 2022 will be identifying and implementing the appropriate technologies to help you ensure business continuity and market positions. Despite the fact that the pandemic is not yet completely over, it has had long-term consequences for the global economy and has fundamentally altered the business landscape by introducing digital technologies into the equation of success.
Based on my previous work experience in a bespoke software development company that assists businesses in growing in a sustainable manner, I can predict the significant impact that technology will have on our society in 2022. It is only logical that businesses are now looking for ways to future-proof their products and services in order to remain competitive in the face of an increasing digitalization wave that is gradually disrupting each business sector.
New Тechnology Тrends
Trend 1: Data Fabric
Data has always been critical to the efficiency and effectiveness of operations and strategic decisions. “Making data accessible to everyone, everywhere” has been a top priority for years. Getting access to the right data at the right time across multiple platforms and applications has always been a difficult challenge to overcome. We decided to call both the problems and the solutions “Analytics” because of the way we approached them. Problems that have existed for years have been given new names. While the term “data fabric” is amusing, it is simply the latest way to describe data nirvana in a world where proprietary technology is the norm. In this environment, data fabric remains a pipedream.
Should we keep cleaning, integrating, and presenting structured and unstructured data in the same way? Of course, we’ll use whatever means are most cost-effective to get the job done. However, we should be aware that there are limits to what we can achieve cost-effectively, particularly when pursuing best-of-breed data and applications strategies. The research firm Gartner also claims that data fabrics can “reduce data management efforts by up to 70%.” What in the world is this number that can be calculated?
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Trend 2: Cybersecurity Mesh
Each and every person is well aware that the number and variety of cyber threats are growing. We also understand that there are no perfect solutions – and that there never will be any. We are aware that the majority of businesses do not fully comprehend the threats and, as a result, either underinvest in cybersecurity or invest in the wrong areas. Vendors make statements like the following, which you can read below:
“A cybersecurity mesh is a flexible, composable architecture that integrates widely distributed and disparate security services,” according to the authors.
It is possible to use a cybersecurity mesh to combine the capabilities of best-of-breed, stand-alone security solutions to improve overall security while also bringing control points closer to the assets they are designed to protect.
In both cloud and non cloud environments, “it can quickly and reliably verify identity, context, and policy adherence.”
These are normative and prescriptive statements, not statements that can be taken action upon. “Composable architecture that integrates widely distributed and disparate security services” is, without a doubt, something we want. Who doesn’t want to be a celebrity? Every time we want something, there is a chasm between us and how we can get it. This isn’t a new trend, but rather an old aspiration.
Trend 3: Privacy-Enhancing Computation
How long has it been since we’ve talked about “privacy”? What is it about privacy that makes it such a great bar or party conversation? Because far too many business models are only viable in an environment where there is no privacy. Even worse, how many people in the United States are truly concerned about digital privacy? ) (I am aware that Europeans are more concerned with privacy than Americans, and that privacy is a contentious issue or non-issue depending on where a country falls on the democratic/authoritarian spectrum.) Americans express concern about privacy, but “Despite Privacy Concerns, Consumer-Level Inaction Reigns Supreme,” according to a recent report. However, despite the fact that there is lip service paid to privacy, retailers and other vendors are continuing to take advantage of their access to personal data everywhere and at all times. They are in desperate need of it. They are the ones who pay for it. They are in the business of selling it. ‘Privacy-enhancing computation,’ as defined by Gartner, is a lovely name for an old problem that no one cares enough about to change their online behavior. (And, by the way, where has all the legislation gone that everyone keeps talking about?)
Trend 4: Cloud-Native Platforms
This significant trend is already well underway. The use of cloud-native platforms to build applications built on “containers, microservices, serverless functions, and immutable infrastructure, deployed via declarative code are common elements of this architectural style… these techniques enable loosely coupled systems that are resilient, manageable, and observable” has gained significant traction among companies still struggling to repurpose their application portfolios. Yes. Is this the way things will be in the future? There’s no doubt about it. So, what exactly is new here?
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Trend 5: Composable Applications
As much as anything else, developing an API- and event-driven culture is essential to the development of “composable” applications (and the larger composable enterprise architecture). Furthermore, legacy applications must be preserved as more companies attempt to transition away from old architectures and into cloud-native status without causing too much disruption – a goal that has been in the works for several years. More recently, we’ve added low code/no code for the development of microservices-based applications, with the goal of reusing APIs as much as possible, ideally within a “modern” governance model, to our offerings.
An old goal has been given a new name.
Trend 6: Decision Intelligence
How can this not be considered an homage to analytics in the year 2010? In the year 2021, we will be thinking about automation. This is an old trend with a few slightly new twists on it, as you can see in the photos.
Trend 7: Hyperautomation
This one is about the current state of automation. If you are following the 4IR and the Future of Work, you are already familiar with the concept of automation. As defined by Gartner, “hyper-automation” refers to “a disciplined, business-driven approach to rapidly identify, vet, re-automate, and improve the efficiency of as many business and IT processes as possible.” This is a trend that has been in effect for a very long time. It has been a trend — and an aspiration — for some time to achieve this goal under the umbrella of robotic process automation (RPA), which includes processes that are modeled, mined, eliminated, modified, or automated.
Trend 8: AI Engineering
Best practices for repeatable design, development, and deployment are at the heart of artificial intelligence engineering. OK. Is this, however, a brand-new trend? What about a company that has been around for at least five years and is well-established?
Trend 9: Distributed Enterprises
This is the point at which digital transformation and edge computing collide.
Trend 10: Total Experience
This has been an aspirational goal for a long time. Simply look it up on the internet. Who is the perpetrator? Despite the fact that there are pockets of opportunity such as returning unboxed Amazon items to Whole Foods it remains elusive. Who wouldn’t want seamless, simple, and enjoyable TX?
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Trend 11: Autonomic Systems
Wow. Sure. “Autonomic systems are self-managed physical or software systems that learn from their environments and dynamically modify their own algorithms in real-time to optimize their behavior in complex ecosystems,” according to the Wikipedia definition. What’s the harm in trying? But is there a trend?
Trend 12: Generative AI
It is unquestionably a long-term strategic goal to do so. If only there was a discernible trend in generative AI.
The main problem with Gartner’s (and other companies’) trend lists is that they are inevitably repetitive and overlapping, particularly with previous years’ lists. While things move quickly in the world of technology, major trends – such as application architecture and artificial intelligence – will continue to be “trends” for years to come. “Updates” are interesting, but they aren’t particularly useful. To be sure, there are more people thinking about microservices and containers now than there were last year, and more companies are investing in artificial intelligence pilots. Because it is difficult to describe truly new trends, technology forecasters rename old ones with catchy names to make them more appealing. Some of the names, on the other hand, are just too obvious. Perhaps the trends will be different next year, or the (re)names will be more imaginative. Alternatively, they may simply be referred to as aspirations.
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