6 major data science trends we’re starting to see in 2022

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So far, 2022 has looked to be a year of adaptation as businesses and economies recover from the impacts of the global pandemic. Companies have found it increasingly essential to keep up with consumers’ rapid evolution, needing to evolve just as much alongside them.

This article covers the trends we can expect with such evolution, specifically in the data science sector, which is quickly becoming a powerful tool increasingly used by businesses worldwide. Accelerating innovation within the tech sector is pushing data science in a new direction and providing the means by which consumer data can be analysed more efficiently and effectively.

The biggest data science trends we can expect to keep experiencing this year are:

  1. The use of ‘synthetic data’ to train AI
  2. The implementation of quantum computing to analyse data
  3. A shift towards the decentralised ledger or blockchain to store and send data
  4. The increase in the use of graph technology to process the data and make contextual connections
  5. The movement to storing data in physical assets to avoid latency and regulatory pressures
  6. The ascension of data science to a core business function.

Trend One: Generative AI and synthetic data

Synthetic data is information generated by algorithms or computer simulations that offers an alternative to real-world data. Synthetic data provides an alternative when data is either too difficult to collect or privacy concerns and legislation prohibit it. Through the digital creation of data, businesses can avoid these concerns and train their ML algorithms.

For example, take the emergence of facial recognition. During the infant stages of its development, there was a surge of privacy concerns regarding the use of real-life people’s faces in the training process.

This challenge left companies stuck in an ethical dilemma where progress slowed to a crawl, and it looked almost as if the task was impossible. However, this is where synthetic data overcame this hurdle by generating synthetic images of people who do not exist, allowing for the program to learn and train before being released to the public.

The use of synthetic data is easier, cheaper and more ethical. It is no surprise then that an increase in the usage of synthetic data will continue in 2022.

Trend Two: The role of quantum computing in data science

The data science sector is currently undergoing significant discussions and plans to implement quantum computing in its critical processes. Quantum Computing works by harnessing the laws of quantum mechanics and the ability of subatomic particles to exist in more than one state.

Instead of relying on binary code of just 0’s and 1’s, quantum computers are able to encode data where information can be both a 0 and a 1 at the same time. This allows these computers to solve problems at a much faster rate than traditional computers.

As a result, this improvement is very advantageous for the data science sector. Google is already trying to implement quantum computing using a processor called Sycamore.

However, this type of computing is still very much in its early stages and will require a lot of fine-tuning before it can be fully adopted. All in all, 2022 will most likely be the year when quantum computing becomes widespread.

Trend Three: The decentralisation of data science using blockchain

Blockchain has become widespread in numerous industries over the past few years. In particular, the financial and healthcare sectors have been at the forefront of its adoption. In 2022 the blockchain is making an entrance into the IT sector.

Primarily, the usefulness of this decentralised ledger for data science lies in the challenges it can solve and overcome.

The first is the new methods it provides when managing and transporting big data. Storing data in the blockchain is more efficient and effective, and the decentralised structure allows data scientists to analyse the data directly from their own devices.

On top of this benefit, the blockchain tracks the origin of the ‘asset’ or data, giving more robust security and making it easier to validate the information.

This technology is becoming increasingly appealing to businesses that rely on data analytics, and no doubt the use of blockchain will become widely implemented in 2022.

Trend Four: Graph technology and the importance of contextual connections

Graph technology revolves around making connections within data and highlighting the relationships within massive data sets. This allows for simpler processes that efficiently accentuate the patterns between data points.

While graph technology is not a new ground-breaking way to process data, the commercial opinion on its usage has begun to shift, and the frequency of its use is increasing dramatically – especially over 2021.

This can be partly attributed to the global pandemic which prompted governments to use graph technology to identify common patterns in the spread of the virus, subsequently contributing to our current understanding of Covid-19.

This is because in most cases it doesn’t matter how much data you process, even if it is valuable and structured, often the information is meaningless without context. Graph technologies offer that context.

During this time, the exhibition of graph technology benefits has prompted numerous firms and businesses to reconsider their stance on graph technology. So, expect to see the prominence of graph technology grow over 2022 and beyond.

Trend Five: Data assets and their storage shifting to physical locations

Over the coming year, it is highly expected the industry will witness the move from data analytics living in cloud environments to physical assets.

While this may seem like a minor trend, the implications are pretty substantial.

The new locale will mean reduced or even eliminated latency and it also enables real-time values. Not only this, but the move will provide a solution for legal or regulatory pressures where data can’t be removed from a specific location. The added security and efficiency the move will bring makes this a notable trend in 2022.

Trend Six: Data science becoming a core business function

The benefits and importance of using data analytics in business is becoming immensely recognised. The role data science plays is becoming a core function and is highly valued by firms today. Previously, business leaders underestimated the change data science would bring and those who refused to adopt the innovation missed opportunities and many were left behind.

Now in 2022, data science is recognised as ‘game-changing’ where the accelerating internal innovation feeds a company’s advantage providing the competitive edge needed to succeed. As such, investment in the sector is growing dramatically and will continue to increase in magnitude throughout 2022.

This will carry through to job growth, wage increases and promotions for the individual data scientists who are at the forefront of this innovation. If you want to get involved, book a consult here to see how we can get you the qualifications needed to start your own career in data science.

All in all, 2022 will be a landmark year for data science. The speed of innovation in the sector is driving massive change and large investments.

The trends explored above all point toward increases in demand for data specialists and the skills necessary for businesses to remain competitive. So, get ahead and take advantage of this by getting qualified by completing one of our full-time or part-time courses. Schedule a call today.

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