11.11.2022

Data science and analytics trends for 2023

Data and analytics are what keep social and business networks, loyalty cards, competitions and offers on the internet alive and free for most of us. We either gift it or it is extracted seamlessly without our knowledge. However, whether bought, sold, ‘vacuumed’ or gifted, it is the panacea for not only for the successful modern business, but can be the differentiator between a brand being either successful or a total failure. And it comes from so many sources, providing valuable insight across industry and commerce.

The sensible and moral use in a data-driven business helps ensure that businesses can operate on what they know rather than what they might assume. This transformation is bringing with it both reactions and responses that help turn uncertainty into more of a certainty. And this is even more so when society is disrupted by things such as pandemics and wars. It’s a foolish supermarket that puts Christmas crackers on the shelves in April and ignores the data coming directly to it from its loyalty card.

Data is at the heart of the digital transformation that is occurring and likely to continue apace during 2023. It just keeps moving along at lightning speed, with both improving and new technologies making it all the more efficient, and to be successful, companies have to keep up with this.

Democratisation of data

It is of little value for data scientists and engineers to keep data to themselves. To make the best use of data and the analysis of it, relevant applications, tools and platforms have to be accessible by all staff in a business. This helps the overall efficiency and effectiveness of the business as a whole.

The picture for, 2023 is the realisation that data paints a picture of the customer and can assist immensely in developing the products and services that customers not only want, but actually need. It can also affect bottom-line costs and consequently, bottom-line profitability. But the business as a whole needs to have access for this to work properly.

A perfect example of data at work can be seen on popular retail internet sites. The “people who bought this also bought this”, the “people who looked at this also looked at that” and the “you bought this and may like that” messages we all take for granted as being part of the purchase process. 

Real-time data

Bringing the “data at work” example used above very simplistically to the point of purchase on the retail shop floor is an example of real-time data at work in its most basic form. This, for example, could be, the opportunity to sell a bottle of brush cleaner and canvas varnish to someone originally purchasing just a canvas, brushes and paints.

However, it becomes more complex in the electronic world of data. If you’re looking for current insights, you need to know what’s happening at the moment. Otherwise, it’s so quickly outdated and of no value. Now this can be more costly and may require a more embracing approach to its collection (for example, better IT), but it does mean it’s as up to date as possible. To go back to social networks, Facebook analyses incredible amounts of data to present us with what it deems to be appropriate and relevant advertising at the time. And food delivery sites present foods we like at the time they have worked out is best for us, all based on our most recent purchases.

So, in essence, it can be seen that businesses/organisation with the most up to date data (backed up by a sensible strategy – it’s no good a vegetarian being offered the day’s chicken dish) can quickly gain a competitive advantage. For this reason, real-time data and analytics will prove invaluable for 2023.

Data governance and regulation

No matter where or who you are and what you do, government are increasingly and rightly clamping down totally on illicit personal data usage and are legislating to protect their citizens, as you will already know from the GDPR rules in the Europe and the UK. This will increase throughout the world during 2023, forcing companies to embrace rules and regulations.

This is an important aspect for businesses who use data. Not only will it protect the consumer, but it will mean that businesses/organisations who use our data will, to put it simply, have to concentrate on products and service that are actually needed, rather than showering everyone with irrelevant marketing messages (which sadly will continue via the bane of modern society, spam).

Businesses/organisations will have no option but to ensure they have to audit precisely how they collect, where and how they handle and store data and what they do with it. The consumer needs to know that their data will be looked after and is safe, that there is 100% trust and that they will in fact ultimately benefit.

Artificial Intelligence (AI)

Artificial intelligence (AI) is galloping forward like a million-pound thoroughbred horse. In business, it’s use is in increasing the accuracy of business predictions, eliminating repetitive and wasteful work and enable the workforce to respond immediately, irrespective of their expertise or role in the business. AI (together with Machine Learning [ML]) takes the manual, hard work out of data analysis through algorithms (a list of rules to follow in order to complete a task or solve a problem) that are improving at an exponential rate. Computers can now “see” using cameras and reply in human language that all can understand.

Cloud data services

This is not strictly a stand-alone title, but more of a hand-in-hand title. In this case, it refers to data very much as a service. Using cloud-based services puts data collaboratively at the hands of all who need it, eliminating the cost and management of their own, potentially expensive, in-house equivalent. Usually, on a subscription model (or “pay as you go” for the smaller business), it can include bolt-ons such as analytics. It is actually part of the democratisation of data mentioned earlier. And its all about effectively and efficiently providing valuable insights for the business/organisation to use.