About Data Analysis

Data Analysis refers to the process of collecting and interpreting data to reveal meaningful insights that are then used to make informed decisions. Organisations of all sizes and descriptions now have access to a plethora of data, meaning there are plenty of opportunities for talented data analysts to make their mark. Depending on the organisation you work for, you could be responsible for interpreting sales figures, website analytics or logistics costs and translating this information into actionable business insights. You might uncover, for example, how to reduce an organisation’s logistics costs or how to increase website click-throughs.

　　From spotting trends to making forecasts, data analysts help businesses make better decisions across the board. Whether you’ve got your sights set on Wall Street or a tech start-up, studying Data Analysis can take you to your dream career.

　　

Is Data Analysis right for me?

As you can imagine, Data Analysis is well suited to people with a knack for numbers and spotting patterns. This includes coming to grips with mathematical modelling, analysis, statistics and other methods of manipulating data to extract information. You should also be a detail-oriented person capable of inputting precise queries and identifying any interesting outcomes, no matter how minute or nuanced. Finally, you should also be a strong communicator who is able to translate data to real-world insights that the rest of your team can make use of.

　　In terms of working as a data analyst, you can expect to work a full-time schedule between the hours of 9am and 5pm. In some cases, working overtime might be necessary in order to meet a big deadline or address an urgent business need.

　　

Data Analysis study options and costs

　　Most professional data analysts have a Bachelor’s degree in a field like mathematics, finance, statistics, computer science or economics. Tuition for a degree like this can cost around USD$30,000 a year in the US or £20,000-30,000 a year in the UK.

　　Relevant and up-to-date certifications are important in the world of Data Analysis. This can include the Certified Analytics Professional or Cloudera Certified Associate Data Analyst program, or programming certifications if you’re hoping to eventually become a data scientist.

　　

Future outlook

Data Analysis is only growing in importance, extending to a wide variety of industries beyond tech. In fact, big data analytics is now heavily relied upon in telecommunications (95%), insurance (83%), advertising (77%) and financial services (71%). You can choose to specialise in one of these areas, or even move between industries thanks to your transferable skills.

　　Data analyst jobs in the US are expected to grow 25% by 2029, meaning budding data analysts will be able to enjoy great stability and generous compensation. If you’re looking for even better prospects, consider transitioning to a data scientist role instead, which is expected to grow by 28% in the next five years!

　　

Career pathways for Data Analysis graduates

　　

Data Analyst

　　Data analysts are responsible for analysing industry or company data to identify business opportunities. Because of how essential these skills are, data analysts can also have industry-specific titles like business analyst, intelligence analyst or healthcare data analyst. To get a competitive edge, many data analysts also pick up programming and SQL skills.

Data Scientist

　　Many data analysts progress to becoming data scientists, developing an understanding of machine learning and advanced mathematics to build data-crunching algorithms and predictive models.

Data Engineer

　　Data engineers look at the bigger picture, focusing on large datasets and optimising data analysis processes. Data engineers are also responsible for upgrading database infrastructure to allow for faster and more accurate queries.

Computer Systems Analyst

　　If you’re more digitally-minded, consider using your data analysis skills in the role of a computer systems analyst instead. In this role, you’ll be responsible for maintaining and improving computer systems, evaluating existing systems, proposing modifications and ensuring new systems meet user requirements.