Data analysis is the process of applying statistical analysis and logical techniques to extract information from data. When carried out carefully and systematically, the results of data analysis can be an invaluable complement to qualitative research in producing actionable insights for decision-making.
If that sounds a lot like data science, you’re right! It’s a closely related field, but there are important differences. Data scientists typically come from computer science and programming backgrounds and rely on coding skills to build algorithms and analytic models to automate the processing of data at scale. Data analysts typically have backgrounds in mathematics and statistics, and frequently apply these analytic techniques to answer specific business problems - for example, a financial analyst at an investment bank.
Data analysts don’t do as much coding as data scientists, but it’s still important to know your way around certain programming languages. In particular, SQL (Structured Query Language) is the industry standard for navigating large databases, and statistical programming languages like R or Python are essential for performing advanced analyses on this data.
According to Glassdoor, the average median annual salary for a data analyst was $69,291 as of November 2019. Of course, because data analysis is in demand across a wide range of industries, the salaries of two data scientists with similar job descriptions might be quite different depending on whether they're working with a small startup or a global hedge fund. Around this median, Glassdoor found data analyst salaries as high as $105,000 and as low as $48,000.
As with data science, online courses are a great way to learn data analysis skills, and Coursera offers Professional Certificates, MasterTrack certificates, Specializations, Guided Projects, and courses in data analysis from top universities like Duke University, University of Michigan and companies like IBM and pwc.
As you gain experience as a data analyst, you may encounter opportunities to advance your career in a few different directions. Depending on your goals and interests, you may progress into data science, management, consulting, or a more specialized data role. Read more about the data analyst career paths and salaries in this article.