1. What is the state of the data analytics industry in 2025?
If you’re thinking about becoming a data analyst, you’ll want to know: Is this a smart career move? In the wake of the AI hype of 2023, what can you expect from the year ahead? Let’s take a look.
Are data analysts in demand in 2025?
When considering a career as a data analyst, it’s important to think about the wider context in which you’ll be working.
As individuals, we’re generating masses of data all the time—data that is interesting for businesses and organizations as it tells them something about how we behave in relation to their products or services. The more we rely on digital devices and services, the more data we generate—and, in turn, the more important it becomes for companies to make sense of this data.
The data skills shortage
To give you an idea of just how big the big data market is, it’s estimated that by 2025, it’ll be worth $229.4 billion. What does that mean for you? Well, the data market is growing exponentially, and so is the need for data analysts.
This sentiment is echoed in the World Economic Forum’s Jobs of Tomorrow report (published in 2020), which identifies data and AI is one of seven high-growth emerging professions. Of all seven professions identified, data and AI shows the highest growth rate at 41% per year. As it currently stands, there aren’t enough data experts to meet this need; according to a recent study, employers expect data science and analytics to be one of the most challenging areas to recruit for—second only to cybersecurity.
The rise of big data
All of the most effective and successful products, services, and strategies these days are data-driven—from our understanding of the COVID-19 pandemic to those spot-on recommendations we get from the likes of Netflix and Spotify. Data is everywhere, being generated in huge volumes at a rapid pace. Wherever there is data, there is a need for data analysts.
The advent of the age of AI
Enter the generative AI explosion of last year, as large language models (LLMs) led by Open AI’s ChatGPT, promised to revolutionise things. Not just the tech industry itself, but the possible applications of these spread far and wide, and demand grew immediately for professionals who were equipped to understand them. This truly was the year of the machine learning engineer, a data pro skilled at planning and manipulating LLMs and harnessing the power of generative AI for businesses. Suddenly there are over 15,000 open ML engineer positions on Indeed.com.
So, to answer the question: Data analysts are very much in demand in 2025, and will continue to be for the foreseeable future. Great news for anyone considering a career change!
2. What does a data analyst do?
If you’re looking to carve out a career in the field, it’s important to know what the work of a data analyst entails—and how it differs from other roles.
In simple terms, data analytics is the process of analyzing raw data in order to draw out meaningful, actionable insights. These insights are then used to help businesses make smart decisions.
Tools
Data analysts work with a range of business intelligence and analytics tools. They are typically expected to be proficient in software like Excel and, in some cases, querying and programming languages such as:
- SQL
- R
- SAS
- Python
To work as a data analyst, it’s important that you’re comfortable using such tools and languages to carry out data mining, statistical analysis, database management, and reporting—but we’ll take a closer look at the skills and tools you need to master in section three.
3. What is the typical background of a data analyst?
Now we know, broadly speaking, what a data analyst does, you might be wondering: What is the typical background of a data analyst? What experience do I need?
As we’ve seen, a career as a data analyst will see you bridging the gap between data and business strategy. Data analysts are, therefore, very comfortable working with numbers. They also tend to bring at least some business acumen to the table. In terms of formal education, data analysts typically study related subjects, such as:
- Maths and / or statistics
- Finance and / or economics
- Computer science
- Information management
- Business information systems
However, that’s not to say that you can’t become a data analyst if you don’t possess one of these degrees. There are many other fields of study or professional experience that can prepare you for a career in analytics, including marketing, IT, and customer service—to name just a few.
The most important thing is to master, and demonstrate, the right skills for the job.
4. What skills do you need in order to become a data analyst?
Now we’re getting to the crux of how to become a data analyst. In this section, we’ll outline some of the key hard and soft skills that employers are looking for when hiring data analysts.
We’ve also included some tools and languages that data analysts might work with. Not all of these skills and tools are essential for every data analyst role, but we’ve included those that frequently come up in real job descriptions.
Data analyst roadmap: soft skills
- Communication, collaboration, and presentation skills
- Problem-solving
- Research
- Attention to detail
- An analytical mindset
- An affinity for numbers
- Good organizational skills and an ability to meet deadlines
- Some commercial knowledge or business acumen
- A methodical and logical approach
Data analyst roadmap: hard skills and tools
- Proficiency in Microsoft Excel
- Knowledge of programming and querying languages such as SQL, Oracle, and Python
- Proficiency in business intelligence and analytics software, such as Tableau, SAS, and RapidMiner
- The ability to mine, analyze, model, and interpret data
- The ability to work with large, complex datasets
- Solid understanding of data profiling and requirement gathering processes and principles
- Expertise in data visualization
- The ability to communicate findings and to make actionable recommendations for the business
- The ability to deploy commercially viable statistical models
It’s important to note that data analysts can work in pretty much any sector—from finance to healthcare to marketing and beyond. Most organizations gather raw data and hire analysts to turn it into actionable insights. This means that, in addition to the core skills outlined above, each company will come with its own unique set of requirements.
