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Choosing a career in data analytics

Posted on: June 29, 2023
African American Business Man Analyst Using Data Analytics

In today’s data-driven world, it’s no surprise that data analytics has become an in-demand career path. The ability to analyse and interpret large datasets is crucial for making informed business decisions, which means there is a growing demand for skilled data analysts in a variety of industries, including:

  • Banking and finance.
  • Insurance.
  • Manufacturing.
  • Healthcare and pharmaceuticals.
  • Government.

In fact, according to graduate jobs site Prospects, data analysts are actually in demand across all sectors – and across a range of areas, too. These areas include:

  • Business intelligence.
  • Data assurance.
  • Data quality.
  • Digital marketing and social media.
  • Sales.

Salaries are attractive as well: the National Careers Service lists an average entry-level salary of £23,000 annually for beginners, and rising to an average of £62,000 annually for more experienced analysts.

With so many different paths and specialisations within data analytics, it can be overwhelming to know where to start. In this article, we’ll explore some of the different aspects of data analytics, as well as some of the essential skills and requirements to keep in mind when considering a successful career that features data analysis.

What does a data analyst do?

Data analysts collect, process, and perform statistical analyses on data sets. They are responsible for gathering and organising large amounts of data – big data – from various sources and turning it into valuable insights that can help inform business decisions.

Responsibilities can include:

  • Collecting and cleaning data. Data analysts ensure that data is accurate, complete, and consistent through data cleansing, and that it is stored in a way that can be easily accessed and analysed.
  • Conducting statistical analyses. Data analysts use statistical software and programming languages to analyse data and identify patterns or trends.
  • Creating visualisations. Data analysts often create charts, graphs, dashboards, and other visual representations of their data to help communicate their findings more effectively with stakeholders and business decision-makers.

Data analysts play a critical role in helping organisations make data-driven decisions. By analysing data and providing insights, they help businesses identify opportunities for growth, improve operational efficiency, and better understand their customers.

What are the skills required to be a data analyst?

Successful data analysts need to have a combination of hard skills and soft skills in order to do their jobs.

Essential data analysis skills include:

Mathematics knowledge

Data analysts are typically good with numbers. However, it’s worth noting that mathematical skills is not the most important requirement for a data analyst role. Instead, it’s more important that data analysts know how to think logically, solve problems, and effectively communicate information.

Analytical skills

Data analysts need to have strong analytical and critical thinking skills in order to identify patterns and trends in data, and then draw conclusions based on their analyses. 

Technical skills

Data analysts need to be comfortable using statistical analysis software as well as working with databases and data visualisation tools, such as Tableau

Problem-solving skills

Data analysts need to be able to approach problems with a creative, analytical mindset in order to find solutions to complex problems.

Attention to detail

To ensure that their data is accurate and consistent, data analysts need to pay close attention to detail.

Communication skills

Data analysts need to be able to clearly communicate their findings to stakeholders, often simplifying complex data and information into terms and language that everyone can understand. With this in mind, it also helps to have strong presentation skills.

A commitment to continuous learning

Data analytics is a rapidly evolving field within computer science, which means that data analysts need to become lifelong learners in order to keep up with new trends and technologies.

Coding skills and programming languages for data analytics

Coding skills and knowledge of programming languages are essential data analyst skills. Some of the most common languages, technologies and skill sets used within the data analyst job role include:


Structured Query Language (SQL) is a standardised programming language. It’s commonly used to manage relational databases, and can extract and organise data for analysis.


Python is a general purpose programming language that’s frequently used for data analysis.


Java is a programming language that’s used for a wide variety of applications. This includes data processing and analysis, as well as mobile, desktop, and web applications.


R is a programming language that was designed for statistical computing.


Microsoft Excel isn’t a programming language, however, it is still a valuable tool for data analysis. In fact, many data analysts use Excel to organise and clean their data, and to perform basic statistical analyses.

What is the difference between data analytics and data science?

Data analytics is used for analysing and interpreting data in order to gain insights that can inform and influence business decisions. It typically involves working with structured data and using statistical analysis tools to identify patterns and trends, and then answer specific business questions.

Data science, on the other hand, involves working with all kinds of raw data, including structured, semi-structured, and unstructured data. Data scientists use a variety of advanced tools and techniques, such as machine learning, artificial intelligence, and data mining algorithms, to build predictive data models. Data science is often focused on exploring and discovering new insights and patterns in data, rather than answering specific business questions.

Become a data-led leader

Use data analysis to help organisations make better decisions, gain valuable insight, and secure a competitive advantage by studying the 100% online MSc Management with Data Analytics at Keele University. This flexible, part-time programme has been designed for leaders and aspiring leaders who are aiming to progress into more senior roles, and who want to develop a firm understanding of the strategic and operational challenges in running an organisation, particularly through the lens of harnessing data for success.

Through your studies, you will develop the key skills and attributes needed for a career that combines management with the high-demand field of data analytics – skills and attributes that will set you apart from other management graduates. You will gain the ability to evaluate and apply theories to various contemporary management problems, and develop an appreciation of the social, environmental, and global implications of management studies.

Some of your key modules will include:

  • Visualisation for data analytics
  • Data analytics and databases
  • Financial statement analysis
  • Managing people and organisations
  • Systems design and programming.
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