Top 10 data science trends and predictions to look out for in 2022
Covid-19 has transformed the way humans transact, and now as people approach the end of another turbulent year, everyone is looking ahead to 2022 hoping for a brighter future. With much of the world moving online, e-commerce, cloud computing, and enhanced cybersecurity measures are just the tip of the iceberg when it comes to assessing current trends in data analysis. Data science is one of the powerful technology trends and is reshaping numerous business processes and operations across the world. As the amounts of data continue to grow, companies are looking for new innovative ways to optimize data science. The data science platform market size is expected to grow from USD 37.9 billion in 2019 to USD 140.9 billion by 2024. And, the current BI and analytics software market are valued at 16 billion USD globally. Here are the top 10 data science trends and predictions that will drive the digital world in 2022:
Data Science on The Cloud
The problem lies with collecting, tagging, cleaning, structuring, formatting, and analyzing this huge volume of data in one place. Data science models and artificial intelligence come to the rescue. However, storage of data is still a concern. One of the major data science trends in 2022 is the use of public and private cloud services for data science and data analytics.
Predictive Analytics
The technology will become more immersive and embedded, where predictive analytics capabilities will be blended seamlessly into the systems and applications with which we interact. Predictive analytics will drive use cases in next-gen apps like metaverse applications.
See more: Latin America’s embrace of ecommerce, digital payments marks cultural shift
Actionable Data
Investing in expensive data software will not provide results unless data is analyzed to derive actionable insights. Actionable data empowers you to become a better decision-maker and do what is right for the business. From arranging activities/ jobs in the enterprise, streamlining the workflows, and distributing projects between teams, insights from actionable data help you increase the overall efficiency of the business.
Cloud Automation and Hybrid Cloud Services
The automation of cloud computing services for public and private clouds is achieved using artificial intelligence and machine learning. AIOps is artificial intelligence for IT operations. This is bringing a change in the way enterprises look at data science and cloud services by offering more data security, scalability, centralized database and governance system, and ownership of data at low cost.
Blockchain in Data Science
While blockchain has become a part of FinTech and healthcare industries, it’s now entering the IT industry. So how does blockchain help with data science? Data scientists have to structure the information in a centralized manner to make it ready for data analytics. This process is still time-consuming and requires effort from data scientists. Blockchain can solve the issue effectively.
Focus on Edge Intelligence
Edge computing will become a mainstream process in 2022. Edge computing or edge intelligence is where data analysis and data aggregation are done close to the network. Industries wish to take advantage of the internet of things (IoT) and data transformation services to incorporate edge computing into business systems. It is one of the crucial data science trends to look out for in 2022.
Improved Cybersecurity
As most businesses have been forced to invest in an increased online presence during the pandemic, improved cybersecurity will be one of the top data science trends for 2022. A single cyber-attack can completely derail a business, but how can companies track potential points of failure without massive cost and time investment? The answer to this burning question lies in excellent modeling and a commitment to understanding risk.
See more: Study finds blockchain technology delivers ‘scalable efficient Central Bank Digital Currency’
Small Data and Scalable AI
As a greater amount of the world moves on the web, the capacity to make versatile AI in light of more extensive datasets is a higher priority than at any other time. Albeit the utilization of large information that shows up rapidly is as yet key for making successful AI models, it’s little information that enhances client investigation. It is not necessarily the case that enormous data does not have esteem, however, it is exceedingly difficult to choose significant patterns from such datasets.
Democratizing AI and Data Science
People have already seen how DaaS is becoming famous. The equivalent is currently being applied to AI models also. On account of the expansion popularity for cloud administrations, AI and ML models are simpler to be presented as a piece of distributed computing administrations and devices. It is one of the crucial data science trends to look out for in 2022.
Clinical Cures and Pandemic Control
In the pandemic-struck world, data science and artificial intelligence accepted a very dependable position in getting the most solid data consistently. Aside from aiding in the innovative work of novel treatment methodology, data science offered potential freedoms and wellsprings of data like patient records, COVID count, patient-revealed travel, and so on.
Source: Analytics Insight
