What Does a Data Analyst Do? Your 2024 Career Guide

A data analyst collects, cleans, and interprets data sets to answer a question or solve a problem. They work in many industries, including business, finance, criminal justice, science, medicine, and government.

What kind of customers should a business target in its next ad campaign? What age group is most vulnerable to a particular disease? What patterns in behaviour are connected to financial fraud?

You might be pressed to answer these questions as a data analyst. Read on to learn more about what a data analyst is, what skills you'll need, and how to start on a path to becoming one.

What is data analysis?

Data analysis is the process of gleaning insights from data to inform better business decisions. The process of analysing data typically moves through five iterative phases:

• Identify the data you want to analyze

• Collect the data

• Clean the data in preparation for analysis

• Analyze the data

• Interpret the results of the analysis

Data analysis can take different forms, depending on the question you’re trying to answer. Briefly, descriptive analysis tells us what happened; diagnostic analysis tells us why it happened; predictive analytics forms projections about the future; and prescriptive analysis creates actionable advice on what actions to take.

Data analyst tasks and responsibilities

A data analyst gathers and interprets data to solve a specific problem. The role involves spending considerable time with data and entails communicating findings. 

Here’s what many data analysts do daily:

• Gather data: Analysts often collect data themselves. This could include conducting surveys, tracking visitor characteristics on a company website, or buying datasets from data collection specialists.

• Clean data: Raw data might contain duplicates, errors, or outliers. Cleaning the data means maintaining data quality in a spreadsheet or through a programming language so your interpretations won’t be wrong or skewed. 

• Model data: This entails creating and designing the structures of a database. You might choose what data types to store and collect, establish how data categories are related, and work through how the data appears.

• Interpret data: Interpreting data will involve finding patterns or trends that could answer the question.

• Present: Communicating the results of your findings will be a crucial part of your job. You create visualizations, like charts and graphs, write reports, and present information to interested parties.

What tools do data analysts use?

Data analysts often use various tools to make their work more accurate and efficient. Some of the most common tools in the data analytics industry include:

• Microsoft Excel

• Google Sheets

• SQL

• Tableau

• R or Python

• SAS

• Microsoft Power BI

• Jupyter Notebooks

Data analyst salary and job outlook

The Canadian Government’s Job Bank lists the average salary for a data analyst as $40.87 per hour, with a high rate of $58.00 and a low of $24.00. The hourly rate varies by province [1]. 

Most provinces' job outlook for the next three years is “Moderate” to “Very Good” [1].

Data analyst vs. data scientist: What’s the difference?

Data analysts and data scientists work with data, but what they do with it differs. Data analysts typically work with existing data to solve business problems. Data scientists build new algorithms and models to make predictions. Learn more about the difference between data scientists and data analysts. 

Types of data analysts

As advancing technology has rapidly expanded the types and amount of information we can collect, knowing how to gather, sort, and analyze data has become a crucial part of almost any industry. You’ll find data analysts in the criminal justice, fashion, food, technology, business, environment, and public sectors—among many others.

People who perform data analysis might have other titles, such as:

• Medical and health care analyst

• Market research analyst

• Business analyst

• Business intelligence analyst

• Operations research analyst

• Intelligence analyst

How to become a data analyst

There’s more than one path toward a career as a data analyst. Whether you’re just graduating from school or looking to switch careers, the first step is often assessing your transferable skills and building the skills you’ll need in this new role. 

Data analyst technical skills

• Database tools:  Microsoft Excel and SQL should be mainstays in any data analyst’s toolbox. While Excel is ubiquitous across industries, SQL can handle larger data sets, and experts regard it as necessary for data analysis. 

• Programming languages: Learning a statistical programming language like Python or R will let you handle large data sets and perform complex equations. Though Python and R are among the most common, it’s a good idea to look at several job descriptions of a position you’re interested in to determine which language will most benefit your industry. 

• Data visualization: Presenting your findings clearly and compellingly is crucial to a successful data analyst. 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 the tools used to create visuals.

• Statistics and math: Knowing the concepts behind what data tools are doing will help you tremendously in your work. Having a solid grasp of statistics and math will help determine which tools are best to use to solve a particular problem, help you catch errors in your data, and have a better understanding of the results.

If that seems like a lot, don’t worry; plenty of courses will walk you through the basics of the technical skills you need as a data analyst. This IBM Data Analyst Professional Certificate Course on Coursera can be an excellent place to start.

Data analyst workplace skills

• Problem-solving: A data analyst needs to understand the question being asked and the problem that needs to be solved. They also should find patterns or trends that might reveal a story. Critical thinking skills will allow you to focus on the suitable types of data, recognise the most revealing methods of analysis, and catch gaps in your work.

• Communication: Getting your ideas across to others will be crucial to your work as a data analyst. Strong written and spoken communication skills with colleagues and other stakeholders are good assets in data analysis.

• Industry knowledge: Knowing about the industry you work in—health care, business, finance, or otherwise—can give you an advantage in your work and job applications. If you’re trying to break into a specific industry, take some time to pay attention to the news in your industry or read a book on the subject. This can familiarize you with the industry’s main issues and trends.

Paths to becoming a data analyst

Acquiring these skills is the first step to becoming a data analyst. Here are a few routes you can take to get them that are flexible enough to fit around your life.

• Professional Certificate: Entry-level Professional Certificate programs usually require no previous experience in the field. They can help you learn basic skills like SQL or statistics while allowing you to create projects for your portfolio and provide real-time feedback on your work. Several Professional Certificate programs on Coursera do just that.

• Bachelor's degree: The Government of Canada states a bachelor’s degree in computer science, computer engineering, or mathematics is usually required for data analysis jobs [2]. If you’re considering getting a degree to become a data analyst, focusing your statistics, math, or computer science coursework can give you a head start with potential employers. Many online bachelor’s degrees have flexible scheduling so you can fit a degree around your priorities.

• Self-study: If you want a path that doesn’t include formal training, you can independently learn the skills necessary for data analysis. Get started with this data analytics reading list for beginners. Once you’re ready to start building a portfolio, here are some ideas for data analytics projects.

Data analyst career advancement

Being a data analyst can also open doors to other careers. Many who start as data analysts go on to work as data scientists. Like analysts, data scientists use statistics, math, and computer science to analyze data. A scientist, however, might use advanced techniques to build models and other tools to provide insights into future trends. 

Get started today.

If you’re ready to start exploring a career as a data analyst, build job-ready skills in less than six months with the Google Data Analytics Professional Certificate on Coursera. Learn how to clean, organise, analyze, visualize, and present data from data professionals at Google.