Big Data Industry Predictions For 2023
As with all predictions, we have to take those with caution because some of them might not turn out to be true. And of course real game-changing innovation often comes out of left-field and takes even the most vigilant of seers by surprise. So, if something earth-shattering happens in the upcoming year which shakes our conception of what can be done with data to the core, and I missed it here, blame the crystal ball.
The value of the big data economy will reach $450 billion
The global big data market reached $208 billion in 2020 and is projected for a steady compound annual growth rate of 10%, reaching $450 billion by 2026, according to Expert Market Research.
The growth is mostly attributed to a growing desire to make all business data actionable in a competitive marketplace, with the growth of IoT devices contributing to the expansion of big data solutions.
High volume, high velocity and high variety: one or more of these characteristics is used to define big data, the kind of data sets that are too large or too complex for traditional data processing applications.
The Internet of Things will go mainstream
There are a plethora of wearable and data-enabled devices on the market now. Some are great, some are clearly faddish and lacking in practical use. 2022 could be the year they break out of the gadget-geek and early adopter markets as people’s need to be connected at all times continues to grow. Expect to see (perhaps be crashed into by) your first person wearing smart-glasses in the street pretty soon.
Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets. For example, connected IoT devices are projected to generate 79.4 ZBs of data in 2025.
AI and Machines will get better at making decisions
At the moment, big data generally acts as guidance for decisions that are mostly still made by people. Expect this to change in the near future, as advances in machine learning bring us closer to the point where data-gorged machines are capable of making more accurate and reliable decisions than people (I know, it’s scary!).
The rise of predictive analytics
The practical result of Big Data and Business Intelligence is Predictive Analytics. Many organizations are effectively leveraging various features of Big Data analytics to predict potential future trends. That includes leveraging mountains of market, new customer, cloud, application, social media or product performance data to carryout predictive analytics.
Leading enterprises, SMEs and even startups are using predictive analytics to apply Ai/ML algorithms, carryout predictive marketing & data mining, eliminate bottlenecks and optimize internal processes.
According to a leading report, the global predictive analytics market is forecasted to reach a whopping USD 22 Billion by the end of 2026.
Business intelligence or BI is already bringing changes in multiple sectors, namely marketing, consumer services, customer experiences, and the entire eCommerce segment. The value of the global BI and analytics software market is expected to be 17.6 bn USD by 2024.
The flawless and efficient data processing capabilities of BI software help companies around the world to accomplish their corporate and data goals without any hassle.
Cloud-Native Analytics Will Become Necessary
Gartner says that by 2022, public cloud services will assume a mandatory stance for 90% of data analytics innovation and processes. As data analytics will move to the cloud, cloud-native analytics will become a necessity for all the leaders and industry stakeholders.
Cloud-native analytics will empower the data analysts to align the right services with the right use cases, which might give birth to governance and integration overheads. Apart from an in-depth analysis of the cost and pricing models, the data and analytics leaders will also be required to prioritize workloads to exploit cloud capabilities.
Digital transformation stems from the ability of an organization to combine both automation and digitization.
As the global business landscape becomes more competitive, more sophisticated, and extremely data-centric, Big Data emerges as one of the key drivers of digital transformation. Businesses across the globe utilize huge chunks of unstructured data to discover the hidden patterns in relation to their business models and Big Data becomes all the more important.
Medical Cures and Pandemic Control
In the pandemic-struck world, big data analytics and artificial intelligence assumed an extremely reliable stance in procuring the most reliable information at all times. Apart from helping in the research and development of novel treatment procedures, Big Data offered possible opportunities and sources of the right information, such as patient records, COVID tally, patient-reported travel, etc.
Medical experts use the term “precision medicine“, where medical experts are able to design a highly precise treatment procedure via big data analytics.
Data-as-a-Service (DaaS) is not an entirely novel concept, as it has been in use for quite some time now. DaaS refers to a data management strategy using the cloud for delivering multiple services, such as integration, storage, processing, and analytics. All these services are delivered over a network connection.
However, earlier delivering these services was a daunting task as the network bandwidth was a limiting factor, and data processing capabilities were also limited.
With Big Data analytics, Data-as-a-Service is gaining momentum, and by 2023 the market size is predicted to hit the 10.7 bn USD mark.
Augmented Data Management
Deloitte and Gartner cite Augmented Data Management as the latest technology trend and suggest that coupling it with AI and ML can unlock various benefits for data management.
ADM or Augmented Data Management is an application that enhances the ability to automate data management tasks. Hence, ADM is a worth-betting trendsetter in the big data landscape in 2022.
Cybersecurity Analytics, Blockchain, and Privacy-Enhancing Computation
Cybersecurity strategies that protect traditional perimeters: processing, sharing, transferring, and analyzing are becoming more prevalent among businesses. This proactive approach to cybersecurity is identity-based and uses data collection and analytics (Cybersecurity Analytics) capabilities for faster threat detection and manual security tasks.
Textual analysis will become more widely used
Increasingly, much of the data we are storing for analysis is in an unstructured form. Textual analysis has become increasingly sophisticated in the last few years and that trend will continue. Computers will become more proficient at “reading” a piece of text (or voice converted to text) and spotting themes and sentiments – meaning it can be classified and analyzed in the same way as structured data.
Data visualization tools will dominate the market
Specialized software designed to create visualizations from data, making it easier for us to spot patterns and links between cause and effect, will become increasingly sophisticated and widely used. This market is expected to grow 2.5 times more quickly than that for other business intelligence software products.
There will be a big scare over privacy
Big security breaches, like those suffered by users of Apple, Sony and Snapchat services in recent years, didn’t scare the general public enough to stop them sharing details of their private lives on social media and other web services. In fact it seems that more people than ever believe that giving corporations our personal information is a small price to pay for the convenience and utility offered by new technology. But could we be headed for a “perfect storm” – hackers have shown they are able to compromise even the securest systems, and governments and law enforcement agencies have been slow to clear the hurdles that prevent many breaches from being brought to justice. A devastating hack or information leak might be enough to start changing people’s attitudes and restoring a bit more common sense over how we take responsibility for our own personal data.
Companies and organizations will struggle to find data talent
There are expected to be 4.4 million people employed worldwide in positions directly involved with big data analysis by next year. But this won’t be enough. By next year, 70% of US businesses will either have a data strategy in place or will be planning one for the near future, according to one survey. The number of colleges offering courses related to big data analysis continues to grow rapidly, but there will continue to be a shortage of workers trained in the necessary skills for the foreseeable future.
Big data will provide the key to the mysteries of the universe
The Large Hadron Collider is currently undergoing an upgrade and will resume operation early next year. It currently collects around 30 Pb of information each year from the high-speed proton collisions which take place 600 million times each second in its machinery. This information is analyzed over a network spanning 170 computing facilities in 36 countries making it by far the largest scientific big data experiment ever undertaken. It has already succeeded in identifying a particle which matches the theoretical Higgs boson – a discovery which many have taken to mean we are heading in the right direction in our attempt to understand how the universe works and came to be. When it spins up again, twice as powerful as before, who knows what else it will find?
Wishing you all a fantastic start into 2023, a year that will be amazing for big data. Source
Originally published December 30, 2014 9:18 am, updated January 12 2022 for relevance and comprehensiveness.