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Organisations are increasingly recognising the importance of data analysts. With the right tools and knowledge, a data analyst can transform data into innovative sales strategies, informative customer profiles and successful cost-cutting strategies. Without skilled data analysts, companies can only guess at how to optimise, improve and succeed in business.
This is why, in an increasingly data-driven economy, becoming a data analyst can open doors to exciting role opportunities in almost any industry you're interested in.
Whether you're a beginner looking to get into the field or an experienced professional looking for career advancement, we've created this step-by-step career roadmap to becoming a data analyst.
What is data analysis?
Data analysis is the process of taking raw information – about customers, patterns of digital behaviour, sales, product performance, and more – and turning it into meaningful insights that can be used to implement optimisations.
Data analysts turn this raw data into insights by cleaning, inspecting and transforming it, so it can be used to solve problems, identify optimisations, support decisions and advise on company strategy. The process of taking raw data and using it to find patterns and trends often involves statistics, maths and logic.
Who can be a data analyst?
A data analyst is someone who can do all of the above.
If you're someone who enjoys the challenge of transforming data into actionable insights, then you have the potential to specialise in the collection, processing and interpretation of data for companies.
Every business is built on data, and every set of data needs skilled analysts to turn it into strategy.
Is data analytics a good career?
Data analysts and scientists have many opportunities for growth and attractive salaries across many industries.
According to the World Economic Forum's Future of Jobs Report 2023, data analysts and scientists are among the top roles that are increasingly in demand across industries and countries. While Glassdoor, one of the world's largest recruitment sites, lists the average salary for a data analyst in the UK as £38,144 (as of 2 September 2023), with experienced professionals earning even higher.
Another advantage of a career in data analytics is the opportunity to work in various industries, as organisations across sectors recognise the value of data-driven insights. Data analysts can find employment in finance, healthcare, retail, technology, and many other fields, providing diverse and exciting career paths.
Discover our 100% online BSc (Hons) Data Science course that allows you to study anytime, anywhere, with flexible payment options to make your path to progress easier today.
How to become a data analyst: step-by-step
1. Build a strong foundation in mathematics and statistics
Data analysts need a solid understanding of mathematical concepts and statistical techniques to analyse and interpret data. Pursuing courses in maths, linear algebra, and probability can help you develop these skills.
2. Learn programming languages and tools
Familiarise yourself with programming languages like Python and R, as well as data manipulation tools like SQL. These skills are essential for data cleaning, analysis, and visualisation.
3. Earn a relevant degree
Taking an undergraduate or postgraduate degree in related topics, such as data science or computer science, can set you up with the skills and knowledge you need to become a data analyst.
With LIBF, you can take advantage of flexible online degree programs in data science and computer science, tailored for working professionals. Our online learning approach allows you to study at your own pace, wherever you are in the world, with on-demand exams and online career support.
Ready to kickstart your data analyst career journey? Discover our online undergraduate degree in data science.
Want to apply existing knowledge and unlock new career opportunities? Explore our online MSc in data science.
4. Gain practical experience
The beauty of data analyst projects is that you can often work on them from anywhere at any time – you just need a computer. Once you start acquiring data analyst skills, look for internships, part-time jobs or freelance projects that will allow to apply your knowledge. This hands-on experience will help you build a strong portfolio and make you more attractive to potential employers.
5. Develop your soft skills
Effective communication, teamwork, and critical thinking are crucial for data analysts. If you're already working, look for ways you can develop and practice these skills in your current workplace. Enhance these skills through workshops, online courses, or by participating in group projects. Your current employer might also offer upskilling training in soft skills that you can do alongside your current job.
6. Stay updated with industry trends
Staying up to date with industry trends in data analysis is an effective way of getting ahead of other professionals, especially when applying for new job opportunities. Industry news can give you valuable insights into the latest tools, techniques and best practices in the field of data analysis.
You can stay up to date with industry trends by reading blogs, attending webinars, listening to podcasts and joining professional networks concerned with data analysis. Here are just a few resources to get you started:
Towards Data Science [blog]
KDNuggets [blog]
Analytics Power Hour [podcast]
Super Data Science [podcast]
DataCamp [courses and webinars]
Data Scientist and Analyst [LinkedIn group]
7. Network with professionals
Attending industry conferences, joining online forums, and connecting with data analysts on LinkedIn are all great ways to expand your professional network and learn about job opportunities.
If you're staying up to date with industry trends via blogs, podcasts and webinars, you can also network with other readers and listeners in comments sections and even get to know the hosts via their LinkedIn or social media accounts.
8. Get certificated
Getting certified in data analytics, or in specialised areas of the field, shows employers you're committed to your professional development and have the skills to be certified. Several renowned corporations offer certification courses in data analysis including Google, Amazon, Microsoft, DataCamp and BCS, The Chartered Institute for IT.
9. Create a compelling CV and portfolio
Use your CV to highlight your skills, education, certifications and relevant experience. And then compile a digital portfolio to show your ability to analyse and interpret data – either by showcasing projects you've worked on, or by creating a demo model that highlights what you can bring to a project.
10. Apply for entry-level data analyst positions
With all 9 steps under your belt, you're ready to start applying for entry-level data analyst roles!
If you choose to study a data analyst-related courses with us, you'll have access to online careers talks and one-to-one sessions with career experts to help you prepare for this next stage in your career journey. You can also take advantage of our online job board to help find your very first data analyst role.
You’ll find everything you need to know about studying an online degree with us in our digital prospectus. To receive your personalised prospectus, please fill out the form below with a valid email address.
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The data analyst career path: progression and opportunities
The career path for data analysts is diverse and offers many routes for growth and specialisation. Let's explore some of the key progression options within the field, providing you with a clear roadmap to advance your data analytics career.
1. Entry-level data analyst
The journey to becoming a data analyst typically begins with an entry-level position. As an entry-level data analyst, you'll collaborate with teams under the supervision of senior analysts or consultants. While your responsibilities may vary, they generally include:
Data collection: Collecting data from reliable sources and making sure it's accurate, before recording it in existing databases.
Data cleaning: Making sure the data is high quality and read for analysis.
Exploratory data analysis (EDA): Identifying patterns, correlations, and trends in the data to extract insights that support decision-making.
2. Data scientist
Many data analysts go on to become data scientists. A data scientist uses advanced programming skills and machine learning algorithms, among other tools, to transform large data sets into a format suitable for analysis. Once the data is prepared, a data scientist applies statistical and machine learning techniques to extract valuable insights and develop models that can predict trends that could influence business decisions.
3. Data specialist
Industries such as healthcare, finance, marketing, and e-commerce often require data analysts with deep knowledge and expertise of the field. One of the primary responsibilities of a data specialist is to understand the unique challenges and requirements of their industry. This expertise will allow you to identify relevant data sources, collect and integrate data from multiple systems, and ensure data quality and accuracy. By gaining industry-specific knowledge, you'll position yourself as a specialist who can provide actionable insights and drive data-led decisions.
4. Manager
Management roles are often the next step up from specialised data positions. While specialised data positions focus primarily on the technical aspects of data analysis, managers require a combination of leadership skills, strategic thinking, and in-depth knowledge of data-related concepts. As an analytics manager, you'd be responsible for leading a team of data analysts or data scientists, as well as collaborating with stakeholders across the organization to understand their data needs and align analytical projects with business goals.
Key skills and qualifications for data analysts
No matter what your chosen career path is, developing a well-rounded skill set can help you succeed. For data analyst roles, here are some of the key skills that can help make you a strong candidate in interviews.
What qualifications do I need to be a data analyst?
Having a relevant undergraduate degree in a data-related field can increase your chances of securing a data analyst role. Although it is possible to enter the field without a degree, and there are several respected certification courses online.
Do I need an undergraduate degree to become a data analyst?
Anaconda surveyed 3,293 people from 133 countries working in data-focused roles for their 2022 State of Data Science report and found that 80.71% of respondents had at least an undergraduate degree.
So, whether you choose an undergraduate degree in data science, computer science, statistics or information systems – getting a degree gives you opportunities to grow your network, pick up relevant skills and learn soft skills such as collaboration, leadership, critical thinking and presentation skills.
Do I need a postgraduate degree to become a data analyst?
In the 2022 State of Data Science report from Anaconda, 33% of respondents held a postgraduate master's degree compared to 57% of US respondents in the Burtch Works Data Science & AI Professionals Salary Report.
As the complexity of data grows with technological advancements, a postgraduate degree can help you acquire more specialist skills to advance your career and support your opportunities for specialisation.
What degrees can help you stand out in the data analyst job market?
To succeed in becoming a data analyst, you'll want to find a degree that gives you advanced technical skills in areas such as statistics and statistical analysis, data visualisation and secure data management. You'll also benefit from a degree that provides context around business, finance and marketing, and the opportunity for specialisation in areas such as logistics and healthcare.
On our data and computer science courses, you'll learn technical skills in Python programming, statistical analysis, data visualisation and machine and deep learning algorithms. While developing soft skills in logical reasoning, creativity in data exploration and communication skills to explain complex data sets.
How LIBF can help you succeed in your dream career
As an LIBF student, you'll benefit from 140 years of experience in higher education and the freedom to choose where and when you want to study. Your digital learning platform is available 24/7, allowing you to access study materials at a time that suits you, and even schedule your exams at any time, day or night. When you study with us, you'll join a global network of industry professionals, current students, alumni and academic staff ready to support you on your path to becoming a data analyst.
With full and part-time online study options, you have the freedom to choose where and when you want to study, and you also have full flexibility over how you pay for your course, with flexible payment plans available for self-funding students and discounts on payments up front.
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