The shift towards a digital landscape has become even more accelerated in the last two years because of the COVID-19 pandemic. Since most of the workforce had to shift online, the importance of data security and cybersecurity became more critical than ever. Even though the world has been opening up again in the last few months, many companies still choose to operate via a virtual workspace or by using a hybrid model where their employees can come only for a certain period of time or only when they are needed in the office.
This evolution of the work model has helped accelerate the dependency on digital resources, which means the value of data science and artificial intelligence has grown exponentially. The most significant trends in data science in 2022 can be identified as becoming the crux of all operational capacities in offices. The primary focus lies in streamlining business value for companies in the virtual space, speeding up the changing dynamics and the online distribution of everything in the organisation, such as data and insights.
So what are the most prominent data science trends for 2022? What can organisations, their employees and developers expect from the next year? Read on to find out.
Top Data Science Trends of 2022
The Rapid Shift to a Cloud Environment
Over 80% (IDC) of CIOs of top tech companies said that their primary focus in data science for this year was to shift to a cloud-based environment. As mentioned earlier, this shift has been accelerated due to the change to a virtual workspace for a majority of the companies. A cloud-based operating system helps companies access their data and information from anywhere around the world, and it also helps improve their existing communication models at their organisation. On-premise applications will soon become a thing of the past as more and more companies adopt a hybrid work model that will enable all data to be accessed virtually. For the last few years, this data science news has been a trend, but it has become increasingly accelerated due to the current COVID-19 climate.
The Increasing Importance of Big Data Optimization
Another data science trend of 2022 that has been observed is the rising importance of optimising Big Data. This means improving the organisational access to Big Data for employees to make it into an integrated resource. The data science and analytics trends predict that Big Data will become one of the most valuable resources for companies in the next year, which means they will have to take particular security, authentication and processing measures to make it more actionable and usable for all. Soon accessing and analysing Big Data won’t be something that only data scientists will be able to do. It will become more democratised and easier to understand for all the employees in the organisation.
Data Becoming a Service
This data science trend of data becoming a service (DaaS) has rapidly increased since the COVID-19 pandemic hit. A lot of consumer data was being shared to expand the reach of valuable information to spread awareness, which showcased the world that sharing data can actually add value and utility. It gives rise to a different problem altogether because data privacy has become an even bigger issue that needs to be addressed appropriately.
Consumer data is sold across platforms and companies, which is a problem for most users because they do not feel safe sharing their personal information and accepting cookies due to a rising risk of getting hacked or having their identity stolen. We have all been subjected to the DaaS concept, with 83% (Cloydwards) of individuals who participated in this survey admitting that they had seen targeted ads across platforms based on their search and user history.
The Integration of Big Data and the Internet of Things (IoT)
The adoption of IoT is also a rising data science trend of 2022, again due to the state of how offices have evolved because of the COVID-19 pandemic. It allows users to access information and data virtually by using physical networks that are embedded with different software. It has become more integrated with data science tools such as AI and machine learning tools to improve the platforms’ flexibility and ease of use. Large scale corporations have already integrated their Big Data with IoT for their operations. Still, a rising data science trend that has been observed and will continue to grow in 2022 is the adoption of IoT for small and medium sized businesses.
Filtration of Big Data
Data science trends dictate the importance and growing usage of Big Data in daily operations for organisations. But one of the data science facts is that just having access to Big Data is not enough anymore. Companies take up a lot of resources to analyse and filter through all the collected data they have, which is expected to reduce in 2022. Data science services are constantly improving to allow companies to filter the data preemptively before analysing it for use.
Augmented Operations for the Digital Workforce
The biggest fear with all the data science news about integrating AI and machine learning in organisations was that it would cost employees their jobs and increase the global unemployment rate. But this is not the case that is being observed in the data science world. AI and machine learning are becoming a crucial part of today’s digital workforce operations. Instead of hindering job growth and opportunities and leading to job loss, they actually enable a more robust digital workforce. AI tools work alongside the human workforce to improve the augmented operations at their organisations to create a seamless and hassle-free experience for all the employees at the company. These data science trends focus on creating a hybrid work model where the evolving cognitive technologies can provide a support function to the employees instead of replacement.
Increase in the Usage of Low Code Artificial Intelligence
While Python will still continue to remain the most popular programming language, there has been a rise in the adoption of low code AI tools as a part of data science services. A big reason for this data science trend is the difference between the demand and availability of data scientists available in the job market. Companies have more vacancies for data scientists than there are in total to fill out the role, so they have to get creative with their processes. They started to adopt low code to no code AI tools that come with pre-installed components to analyse and use their data to generate insights, forecasts and more. Now, they can customise their applications and use them without writing extensive code.
Optimisation of Cybersecurity
Over the last four years, the cybersecurity market has been valued at over $1 trillion (Embroker) globally, giving the industry an average of 12-15% compound growth rate annually. Small and medium sized businesses have also started to realise the importance of focusing on improving their existing cybersecurity measures so that their users and consumers feel safe and their data is protected and valued. Cyber threats and attacks have grown exponentially in the last few years, and hackers have been targeting SMEs for their attacks because large scale enterprises have solid firewalls and other cybersecurity measures to keep their data and operations safe. This is one of the data science trends that will continue to grow in the coming years because of its necessity in the virtual world.
Read also: The Biggest Trends in Data Analytics Forecasted for 2022
Increase in the Usage of Blockchain for Managing Data
Blockchain has evolved from being just a source of cryptocurrency in the FinTech world to being adopted across various other subsets of the IT industry. It helps decentralise and protect Big Data, making it easier for companies to manage. Data scientists will be able to run their data analytics processes directly from their devices because of the decentralised structure of Blockchain. It reduces the dependency on physical networks and servers, which also helps them improve the validation accuracy of their analysis.
Creation of Measures to Make Artificial Intelligence More Scalable
TinyML is a reasonably new data science trend that will soon blow up in 2022. It is a type of machine learning service that can be embedded into any hardware because of its small size. It is cost-effective and versatile, which makes it extremely easy to access for users around the world. This is one of the biggest trends that data analysts, data scientists, business intelligence professionals and AI professionals are looking forward to in the upcoming years.
Conclusion
Overall, the data science trends for 2022 showcase that the adoption of AI and cloud in companies of all sizes will continue to grow in the coming years, with a strong focus on data protection, data privacy, and scalability of artificial intelligence and machine learning tools. Cloud-native solutions soon become a necessity for companies, and the shift towards building a safer virtual environment for all will become more critical than ever.
