Data Science and Analytics Trends of 2022, So Far
The ideas of data science and data visualization have been around for decades. However, their applications have only become useful recently.
In 2022, we now have countless applications of data science and analysis, both big and small. And in an area of such diverse use-cases, even highly-skilled professionals can struggle to know what’s new from one week to the next.
This post will just sketch out a few of the current trends in data science. It won’t give you a comprehensive overview of the subject – but will give you enough information to get excited about data!
Current trends in data science are great news for anyone thinking about taking up any kind of data science course. If you’re taking the first steps in your career now, you’ll find many ways to use your knowledge: and many more ways that it will garner support in the future.
Small-scale data is becoming more important
Data science is naturally a companion to big datasets.
However, now that AI technology is so common in the technology we use every day, we are seeing more and more applications of ‘small’ data.
- Checking the smooth running of a particular part of a factory process;
- Managing one intersection of a traffic system;
- Tracking goods on a shelf;
- Monitoring hospital systems with dynamic human input.
Such applications of data science don’t need huge computing power. The hardware in the device on your product is enough. The outcomes are highly localized, with a small but significant impact on the world around them.
But with all these applications, we need more data scientists to ensure that the systems of all systems are functioning properly.
Improving knowledge of how to fight fraud
Most of us are excited about the ways that data science and analytics can help solve human problems. But we also have to recall that this expertise can be harmful, too.
For example, data science provides the principles that underpin deepfakes: the processes that can help make Mike Tyson look like Oprah Winfrey, or Jordan Peele speak like Barack Obama.
As entertaining as deepfakes can be, they are also extremely harmful – potentially ruining lives, undermining authority, and committing fraud.
Yet in a more normal setting, DS is a massively valuable tool in fighting fraud in our day-to-day lives. Banks can now gather plenty of useful information about normal use transactions – processing user information to see whether a ‘scam’ is normal or not.
Increased attention from businesses and researchers mean that they will become more efficient, more effective, and more common.
Data visualisations are adapting to a new media landscape
The multimedia experiences of web 2.0 have made infographics more popular than ever. Data visualization is one of the more beautiful outputs from a core of data science.
But now, data scientists are adapting to a new situation: in which video-based platforms like youtube and tiktok are increasingly used as a go-to source of information for a younger generation.
Practitioners like the.data.guy are producing content that show how dynamic video can be used to produce remarkable visualizations.
Creative data scientists are more needed than ever in 2022.
Demand for data scientists continues to be strong
If you’re thinking of moving into a career in data science, the statistics are on your side. Data science job opportunities continue to grow globally, suggesting that a data science course continues to be a valuable investment.
For example, In the USA, more than 80% of data teams were looking to hire more data scientists in the first quarter of 2022; and in Singapore in the same year, data scientists were some of the most sought-after tech jobs.
Of course, no educational course is a guarantee of success, and ‘soft skills’ are still required even from exceptional candidates. Keep in touch with the basics: work on your communication skills as well as your technical skills, to become a fully-rounded person.
The educational opportunities for data science and data analytics are huge
With the steady growth in job opportunities, it’s not surprising to find that there are so many educational opportunities in data science.
Indeed, the training routes for data science and data analytics show off the range of learning styles that you can follow. You can learn online, or in real life; with informal certification, or traditional undergraduate and postgraduate degrees; awarded by major institutions and startups.
But some options will be better tailored to you than others. If you’re in Singapore, for example, the MAGES immersive programme would offer a great training for students with a Singaporean educational background. With expert tuition in small teacher to student ratios, it’s well worth considering.
If you’re using a smartphone, checking online banking, or applying a filter to an image – you’re making use of data science and analytics.
More and more of our devices and experiences need to be integrated, starting what some have called a ‘big convergence’ of digital life. Safe and fluid movement of data is fundamental for this process.
With so many processes relying on data, it’s essential that our methods adapt to small-scale problems. Big data is not a ‘one size fits all’ solution. And we are only just learning how the processing of data might be different for every user: for example, using Machine Learning technology with different languages.
But with a growing range of niche specialisms, applying to small businesses and specific industries, there’s no question that this will continue to be a growth area. Getting a qualification in data science will certainly help you out in the long term.