What does a data analyst do?

What is data analysis?

Data analysis is the process of extracting insights from data to make better business decisions. The process of data analysis typically goes through five iterative phases:

• Identifying the data to be analysed
• Identify the data to be analysed
• Identify the data to be analysed
• Identify the data to be analysed
• Preparing the data for analysis 

Data analysis can take different forms, depending on the question it is trying to answer.  In short, descriptive analysis tells you what happened, diagnostic analysis tells you why it happened, predictive analysis makes predictions about the future, and prescriptive analysis gives actionable advice about what to do.

Data analyst roles and responsibilities

A data analyst is a person whose job it is to collect and interpret data to solve a problem. The role involves spending a lot of time with the data, but also communicating the results.  

Data analyst tasks in everyday life:

• Collecting data: analysts often collect data themselves. This may involve conducting surveys, tracking visitor characteristics on a company website, or buying data sets from data collection specialists.
• Data cleaning: Raw data may contain duplicates, errors or outliers. Data cleaning means maintaining the quality of the data in a spreadsheet or through a programming language so that your interpretations are not incorrect or skewed.
• Model data: this means creating and designing database structures. You can choose what types of data to store and collect, determine how data categories are related to each other, and work out how the data actually appears.

Data interpretation.
Communicating the results of your findings will be a key part of your work. You can do this by compiling visualisations such as charts and graphs, writing reports and presenting the information to stakeholders.

What tools do data analysts use?

During the data analysis process, analysts often use a variety of tools to make their work more accurate and efficient. The most commonly used tools in data analysis include:

• Microsoft Excel
• Google Sheets
• SQL
• Tableau
• R or Python
• SAS
• Microsoft Power BI
• Jupyter Notebooks

How to become a data analyst

There are several paths to a career as a data analyst. Whether you're just graduating from school or looking to change careers, the first step is often to assess what transferable skills you have and build the new skills needed in your new role.

Technical skills for data analysis

Database tools: Microsoft Excel and SQL should be the basics of any data analyst's toolkit. While Excel is ubiquitous across industries, SQL is suitable for handling larger data sets and is widely considered necessary for data analysis.
Programming languages. Although Python and R are among the most widely used, it is worth looking at the job descriptions of several positions that interest you to decide which language will be most useful in your field.
Data visualisation. Knowing how best to present information through charts and graphs will ensure that colleagues, employers and stakeholders understand your work. Tableau, Jupyter Notebook and Excel are among the many tools used to create visualisations.
Statistics and maths. A thorough knowledge of statistics and mathematics will help you determine which tools to use to solve a problem, help you spot errors in the data, and give you a better understanding of the results.

Data analyst job skills

Problem solving: data analysts need to have a good understanding of the question asked and the problem to be solved. They should also be able to find patterns or trends that may reveal a story. With critical thinking skills, they will be able to focus on the right types of data, recognise the most revealing methods of analysis, and identify gaps in their work.
Communication: being able to communicate your ideas to others will be key to your work as a data analyst. Strong written and speaking skills to communicate with colleagues and other stakeholders are a good skill for data analysts.
Industry knowledge: If you know the industry you work in - healthcare, business, finance or other - it will be an advantage when applying for jobs and positions. If you are trying to break into a particular industry, take some time to follow industry news or read a book on the subject. This will give you an insight into the main issues and trends in the industry.

Pathways to becoming a data analyst

Mastering these skills is the first step to becoming a data analyst. Here are some of the paths you can take to acquire them, which are flexible enough to fit into your life.

Professional certification: entry-level professional certificate programmes generally do not require previous experience in the field. They can teach you basic skills such as SQL or statistics, while giving you the opportunity to create projects for your portfolio and get real-time feedback on your work. Coursera's many professional certificate programs do just that.
If you're looking for a data analytics degree, courses that focus on statistics, maths or computer science can give you an edge over potential employers. Many online bachelor courses have flexible timetables, so you can tailor your degree to your priorities.
Self-learning. Start with our data analysis reading list for beginners.