I think it’s fair to say that 2024 was a pretty big year for the sexiest job of the 21st century. But what kinds of data trends will there be in the industry in 2025?
Which kinds of tools should you be looking to add to your skillset? How will new advances in data analytics affect your career path?
Wonder no more, as I’ll give you a rundown of six data analytics trends to be aware of this year:
- Artificial intelligence
- Data democratization
- Data unification
- Data-as-a-Service & low-code analytics
- Data governance
- IoT and real-time data
- Data trends final thoughts
1. Artificial intelligence—Everywhere? All of the time?
While it seemed like AI exploded out of nowhere in 2023 (apart from when I predicted it in my 2023 predictions video, but enough about me), those in data circles have been aware and working with it for quite some time, mostly through the field of machine learning.
Data analytics is evolving alongside the growth in AI, and this allows data professionals and other workers to be more productive. The market is now flooded with loads of great new A.I. data tools, which are easily integratable into your data analytics pipelines.
In 2025, expect further saturation of AI. This will take many forms, from hyper-personalization (A.I. assisting marketing analysts to personalize customer experiences), further embedding of LLM into products & services, AI governance, legal challenges to AI training (The New York Times is just the latest company to sue OpenAI for using their articles to train ChatGPT), and more besides!
Further reading: Expert Interview: Beyond the Buzzword – Understanding the Ethical Implications of AI
2. Data democratization
This data trend has been growing over the past number of years, but with the increased ability of AI-charged tools, expect there to be a lot more of this in 2025.
But what is data democratization? Data democratization means giving access to data to all members of staff, whether they be technical employees or not.
Now why would you do that? Well, data-driven decisions make for better business choices. This means relying on data rather than relying on your intuition.
It’s why more and more companies are providing in-house training to educate their staff on data literacy. What is data literacy? It just means that all your members of staff should be familiar with the techniques and principles of working with data.
A simple way to improve your data literacy skills is with this free data analytics short course. Once you’ve completed it, you’ll be in a position to facilitate data democratization in your circle and maybe start your own data analyst career.
Which brings me nicely on to an important clarification.
Data democratization doesn’t mean that data analysts are going anywhere. Just because data’s being democratized doesn’t mean we don’t need technical expertise. Technical experts are still required to oversee data analytics pipelines, for example, and to help mentor and provide support to non-technical members of staff.
We can see examples of the rise in data democratization by the rise in popularity of dashboarding tools like Looker, Tableau and Power BI. But it’s not just analytics departments that are taking advantage of data. Departments like marketing, growth, and product also have a need for data democratization, and this can be seen in the rise of tools supporting these areas, such as:
- AB Tasty for AB tests
- userflow or userpilot for guided onboarding
- Mixpanel or Heap for product analytics
3. Data unification
If you’ve ever worked for a medium-to-large company, you’ll probably have come across the issue of “silos”. This is where, typically due to organization, one team or department has no communication/idea what the others are working on.
This lack of joined-up thinking can lead to big issues. In short, silos mean that you’re not getting the full benefit of your company’s talents. It’s the same with data—there can be different departments all working off of separate data sources, often with different tools.
Data unification is the strategy which seeks to fix that. It functions by bringing together data from multiple sources into a single, consistent, and trustworthy format.
The rise of strategies such as data democratization mean that there is a whole lot more data being used across every single part of the business. On top of that, the fact that data-driven decision-making is common in many organizations means there is a huge need this year for unified data in order for a business to successfully make such decisions.
So why is this year going to be a big year for it? Here’s data expert Alex Freberg (you may recognise him better by his popular YouTube channel, Alex the Analyst) with his thoughts:
In 2025, data unification is expected to continue evolving towards more advanced and automated solutions, primarily in the cloud. More companies are already finding it easier to combine all of their data in the cloud vs. the on-premisis servers they’ve had for the past 20 years.
With this brings new challenges like security and compliance for their data, but most companies are willing to offset those risks as they’ll be able to utilize 80% of their data rather than the 40% when their data was siloed.
Basically, data unification isn’t just a technical exercise to be carried out: Like data democratization, it’s a transformative strategy across the whole business. And data analysts will be right at the heart of it. Expect to be implementing and getting to grips with tools such as Microsoft’s OneLake.
4. Data-as-a-Service (DaaS) & Low-code analytics tools
The future of data analytics will not be the same as the present. Previously, if you wanted an effective data analytics solution, you’d normally need to hire a few data engineers to create your data pipelines, as well as a few data analysts to analyze the data within and create effective data visualizations to share with the wider business.
This can be a restrictive expense for many businesses starting out. It’s also not easy to hire the tech talent you need. And this is where DaaS comes to help. Data-as-a-Service (or DaaS for tools which allow users to manage their analytics requirements such as data warehouses or business intelligence tools. Think DataBricks, Oracle, Dataiku etc
DaaS should ultimately lead to an increase in productivity for small and mid-sized firms because you don’t need to hire as many data engineers, software engineers and data analysts as before.
The use of DaaS in big data analytics will allow analysts to share data more easily than before and will simplify business tasks and processes as more businesses integrate their products and services into the cloud, so DaaS has become a more common method for integrating, managing and delivering data analytics services.
Low-code and no-code data analytics
Furthermore, in recent times we’ve seen the growth in a new type of product—the so-called low-code or no-code analytics platforms.
These are platforms for users who have no coding background, usually involving drag-and-drop interfaces. It allows users to create analytics, pipelines and visualization dashboards without any technical background.
This has further removed barriers to entry for small- to midsize firms looking for data-driven decisions but who don’t have the budget to hire a large suite of in-house analysts or engineers. Some examples of low or no code analytics platforms include:
5. Data governance
I already mentioned it briefly earlier in relation to two other data trends for 2025—AI and data unification—now let’s take a look at data governance, set to be a hot topic this year.
As we all know, more and more data is both being produced and consumed. Along with the rise and data governance comes the rise in concerns of individuals about how their data is being produced and consumed. This is where data governance comes in.
So what is it? Data governance means ensuring that the data that you create is of high quality and ensuring that that data meets all the requirements of the necessary regulations of the area in which the data is both produced and consumed. Basically, let’s make good-quality data and let’s not break any laws.
All firms these days should take care to create a good data governance strategy. A good strategy ensures data protection and tries to ensure that data is of the highest quality possible. Not having a strategy can result in poor-quality data missing out on business opportunities, and in the worst case, incurring regulatory fines or even jail time.
But companies aren’t the only ones who face data governance problems. Consumers also have that burden of responsibility to bear. Quick question—when was the last time you actually read the terms and the conditions of a contract on an app that you use or update? I know it’s hard to do that, and that’s why legal tech firms all across the globe are springing up to help us meet our data governance challenges as private consumers of data.
As a result, I can see a niche in the future for disruptive legal tech firms, helping consumers to understand their contractual requirements using AI and other machine learning. There are already some players already in this space, for example Contractbook.
6. Internet of Things and real-time data
Next up, we have the rise of IoT and real-time data. By now, most of you will have heard of the rise of the Internet of Things, also known as IoT. Whether it’s your robot vacuum, your smart speaker, or even your toothbrush, hardware is increasingly used to track and analyze human behavior.
The rise of IoT means that more products and services are generating real-time data. Real-time data is typically unstructured and high in volume. That means you get a lot of it, and it’s very, very messy. But if you know how to work with unstructured, real time data, you can find invaluable insights into the world that will allow you to add real business value.
So why is this relevant for data analysts? Well, the more real-time data we can capture about the users of any given system, the better we can understand them. Consequently, data analysts will be able to unlock new areas of value for the business that they work in.
With the rise of IoT and real-time data comes concerns with data privacy. I predict that we’ll see an associated rise of more effective data anonymization tactics.
Data trends final thoughts
Data analytics is a fast-paced, ever changing industry, one that will always keep you on your toes. The past year has really underlined that point, with AI making it seem like everyone’s world was about to get turned upside-down.
And that’s why I hope this collection of data trends is helpful to you and will set you up for success in 2025 and beyond.
Are you looking to kick-start your career in data analytics but aren’t sure where to begin? Well, we’ve got you covered. CareerFoundry has a free online data analytics short course that will allow you to dip your toes into this exciting field.
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