As with all predictions, we must approach these with caution, as some of them may not come to pass. Moreover, true game-changing innovation frequently emerges unexpectedly and catches even the most astute predictors off guard. Therefore, if something earth-shattering occurs in the upcoming year that fundamentally alters our understanding of what can be done with data and I missed it, blame the crystal ball.
The value of the big data economy will reach $450 billion
According to Expert Market Research, the global market for big data reached $208 billion in 2020 and is projected to grow at a compound annual rate of 10%, reaching $450 billion by 2026.
The expansion of big data solutions is largely attributable to a growing desire to make all business data actionable in a competitive market, with the growth of IoT devices also contributing.
One or more of the characteristics of high volume, high velocity, and high variety are used to define big data, which are data sets that are too large or complex for traditional data processing applications.
The Internet of Things will go mainstream
Currently, the market is flooded with wearable and data-enabled devices. Some are excellent, while others are clearly trendy and devoid of utility. As people’s need to be constantly connected continues to grow, 2022 could be the year they break out of the gadget-geek and early adopter markets. Expect to encounter your first person wearing smart glasses on the street in the near future.
Mobile data traffic growth, cloud computing traffic growth, and the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the growing size and complexity of data sets. In 2025, connected IoT devices are anticipated to generate 79.4 ZB of data.
AI and Machines will get better at making decisions
Currently, big data serves primarily as a guide for decisions that are predominantly still made by humans. Expect this to change in the near future, as advances in machine learning bring us closer to a time when data-hungry machines can make more accurate and trustworthy decisions than humans (I know, it’s terrifying!).
The rise of predictive analytics
Predictive analytics is the practical result of Big Data and Business Intelligence. Numerous organizations effectively utilize various Big Data analytics features to forecast potential future trends. This includes employing predictive analytics on mountains of market, new customer, cloud, application, social media, and product performance data.
Leading corporations, SMEs, and even startups use predictive analytics to implement AI/ML algorithms, conduct predictive marketing and data mining, eliminate bottlenecks, and optimize internal processes.
The global market for predictive analytics is expected to reach a staggering USD 22 billion by the end of 2026, according to a leading report.
Business intelligence or BI is already affecting multiple industries, including marketing, consumer services, customer experiences, and eCommerce as a whole. By 2024, the global market for BI and analytics software is anticipated to be worth USD 17.6 billion.
The flawless and efficient data processing capabilities of BI software enable businesses around the globe to achieve their corporate and data objectives without difficulty.
Cloud-Native Analytics Will Become Necessary
By 2022, public cloud services will be required for 90% of data analytics innovations and processes, according to Gartner. As data analytics migrates to the cloud, cloud-native analytics will be required for all industry leaders and stakeholders.
Cloud-native analytics will enable data analysts to align the appropriate services with the appropriate use cases, which may result in governance and integration costs. In addition to conducting an in-depth analysis of cost and pricing models, data and analytics leaders will need to prioritize workloads in order to maximize cloud capabilities.
Digital transformation results from an organization’s capacity to combine automation and digitization.
Big Data emerges as one of the primary drivers of digital transformation as the global business landscape becomes increasingly competitive, sophisticated, and data-centric. Big Data becomes even more crucial as businesses around the world utilize massive amounts of unstructured data to uncover hidden patterns in relation to their business models.
Medical Cures and Pandemic Control
Big data analytics and artificial intelligence assumed an extremely dependable position in the pandemic-ravaged world for acquiring the most trustworthy information at all times. In addition to aiding in the research and development of novel treatment procedures, Big Data provided potential opportunities and information sources, such as patient records, COVID counts, patient-reported travel, etc.
The term “precision medicine” is used by medical professionals when they are able to design a highly precise treatment procedure using big data analytics.
Data-as-a-Service (DaaS) is not an entirely novel concept, as it has been utilized for a considerable amount of time. DaaS refers to a data management strategy that delivers multiple services, such as integration, storage, processing, and analytics, via the cloud. All of these services are provided through a network connection.
However, delivering these services in the past was difficult due to network bandwidth constraints and limited data processing capabilities.
Data-as-a-Service is gaining momentum as a result of Big Data analytics, and its market size is projected to reach 10.7 billion US dollars by 2023.
Augmented Data Management
Deloitte and Gartner cite Augmented Data Management as the most recent technological trend and suggest that combining it with AI and ML can unlock numerous data management benefits.
ADM, or Augmented Data Management, is an application that facilitates the automation of data management tasks. Therefore, ADM is a trend-setter worth betting on in the big data landscape in 2022.
Cybersecurity Analytics, Blockchain, and Privacy-Enhancing Computation
Businesses are increasingly implementing cybersecurity strategies that protect traditional perimeters: processing, sharing, transferring, and analyzing. This proactive approach to cybersecurity is identity-based and makes use of data collection and analytics (Cybersecurity Analytics) for faster threat detection and manual security tasks.
Textual analysis will become more widely used
A growing proportion of the data we store for analysis is in an unstructured format. In recent years, textual analysis has become increasingly sophisticated, and this trend will continue. It will be possible to classify and analyze unstructured data in the same way as structured data, as computers will become more adept at “reading” text (or voice-to-text conversion) and identifying themes and sentiments.
Data visualization tools will dominate the market
The sophistication and prevalence of software designed to generate data visualizations, thereby facilitating the identification of patterns and relationships between cause and effect, will increase. This market is anticipated to grow 2.5 times faster than other business intelligence software product markets.
There will be a big scare over privacy
Large security breaches, such as those suffered by Apple, Sony, and Snapchat users in recent years, did not deter the general public from sharing personal information on social media and other web services. In fact, it appears that more people than ever before believe that sharing personal information with corporations is a small price to pay for the convenience and utility provided by new technology. Hackers have proven that they can compromise even the most secure systems, and governments and law enforcement agencies have been slow to remove the obstacles that prevent many breaches from being prosecuted. A devastating hack or information leak could be sufficient to begin changing people’s attitudes and restoring some common sense regarding how we handle our personal data.
Companies and organizations will struggle to find data talent
By next year, it is anticipated that there will be 4,4 million people employed worldwide in positions directly related to big data analysis. But this will not suffice. According to a survey, by next year, 70% of US businesses will either have a data strategy in place or be planning one for the near future. There will continue to be a shortage of workers with the necessary skills for the foreseeable future, despite the fact that the number of colleges offering courses on big data analysis is growing rapidly.
Big data will provide the key to the mysteries of the universe
The Large Hadron Collider is currently undergoing an upgrade and will resume operations at the beginning of the following year. In its machinery, high-velocity proton collisions occur 600 million times per second, generating approximately 30 Pb of information per year. This information is analyzed across a network of 170 computing facilities in 36 countries, making it by far the largest big data experiment ever conducted in science. It has already succeeded in identifying a particle that corresponds to the theoretical Higgs boson; this discovery has been interpreted by many as a sign that we are on the right track in our quest to comprehend how the universe functions and came to be. Who knows what it will find when it spins up again with twice as much force as before?
I wish you all a wonderful start to 2022, which will be an incredible year for big data.