What Is a Data Analyst?
A data analyst is someone who manipulates and studies data and communicates findings with their organization to find opportunities and improvements. A data analyst holds the keys to data-driven business decisions, making it an extremely in-demand role.
What Does a Data Analyst Do?
A data analyst’s duties fall into three key areas.
- Data mining. The analyst pulls information from primary and secondary sources.
- Data cleaning. The analyst cleans the data of any errors or discrepancies and proceeds to find any patterns, relationships, or trends in the data.
- Data visualization. The analyst organizes the data to be easily understood in order to form business goals and strategies.
What Is the Difference Between a Data Analyst and Data Scientist?
A data analyst studies data to extract answers and insights. A data scientist uses data to perform predictive analysis and decide what will happen in the future based on patterns within the data.
Another way to look at it:
- Data scientists ask their own questions to figure out their predictions
- Data analysts are given the questions and expected to discover the answers
Data analysts can be entry-level positions that will grow within the organization, while data scientist roles usually require either advanced master’s degrees or proven expertise with the necessary skills. Data scientists will also have a higher average salary than data analysts.
How to Become a Data Analyst In 4 Steps
- Understand the role. There are many roles within data management and analysis, so it’s important to distinguish what fits you and what you’re looking for. Do the research ahead of time to know what’s expected of a data analyst. Gather information on what technical skills, tools, programs, and communication skills you need to strengthen before applying. This guide is a good start.
- Develop your expertise. The most common way to begin your career as a data analyst is a bachelor’s degree or master's degree in a data-related major. But this is not the only way. Many data analysts start with an online bootcamp or course that teaches technical skills and languages such as SQL, Microsoft Excel, R, or Python. You can also build up to your desired role by getting an entry-level role in IT where you can learn about the organization and get comfortable with various interfaces.
- Find the right people. Your network can unlock many opportunities. Find someone in the field that can act as a mentor or field any questions you may have. You can learn how people got to their current role and different paths you can take. Having a conversation with someone with real-life experience can help you shape your career how you would like. Here's why mentorship in highly technical roles can make a huge difference in career growth.
- Take on projects. In order to land a job as a data analyst, you’ll need to build a portfolio of projects you have done. Find freelance work or team up with a friend whose project might help you grow and apply your knowledge within data science, machine learning, and statistics. These projects will help you not only show proven success in the field but also build your confidence when applying for jobs.
Data Analyst Job Description
A typical data analyst job description might ask for the following attributes, education, and experience:
- Collaborative nature and leadership skills. To be successful within data analytics, focus is crucial. Each organization should have a deep understanding of what they are trying to accomplish, and how data analysis can guide that. It is the role of a data analyst to work with IT, leadership, and data scientists to determine the end result they are looking for in the data.
- Programming language expertise. Every job description will call for proficiency within a few specific programming languages, analytics tools, and database languages such as Microsoft Exel, SQL, R, and Python.
- Analytics experience. A data analyst will be expected to use statistical tools to interpret the data they have gathered, work with the data to find any relevant patterns or trends, and be able to perform predictive analysis. They must also be able to recognize relationships within the dataset and what each relationship could mean.
- Database maintenance. A data analyst will fix any coding errors, track any patterns or trends, delete any irrelevant information to free up space and create any necessary reports to update the team.
A typical data analyst job description will require the following skills:
- Data cleaning and analysis. Data cleaning involves identifying any incomplete, irrelevant, or inaccurate parts of the data set and how to proceed with these errors. Skilled data analysts have a well-trained eye that can recognize blips in the system and have the awareness of how to solve any problems before analysis. Further analysis means understanding how to extract trends and business solutions from data patterns.
- Mathematics and critical thinking. The ability to wield your mathematical skills proves crucial in analyzing and understanding data. An understanding of statistics and probability will allow for the discovery of trends or discrepancies that may appear in data. Critical thinking allows data analysts to hone in on what counts, and not get overwhelmed. A dataset may contain many relationships, errors, and trends, so it’s important to be able to stay centered and keep the main questions in focus while problem-solving.
- Data visualization. A good data analyst must know how to communicate with their audience. Written correspondence, presentation skills, and overall communication skills are fundamental in solving problems with a data set. An analyst must know how to tell a story with their data that can be widely understood and applied, by forming relational databases or graphics, creating presentations, or written reports.
Data analysts also require technical knowledge of industry-specific tools, such as:
- Microsoft Excel & SQL. Microsoft Excel is a widely used jumpoff point for any data analyst. It’s an absolute must in becoming an analyst and is the beginning of understanding data technologies. It’s a light and quick tool for analytics. SQL is Microsoft Excel’s much stronger big brother. It is used to update and communicate with a database, as well as serve as a tool to access and manipulate data.
- R/Python. R and Python are the top two open-source programming languages to provide predictive analytics. The two are very dynamic programs with new features being added very often, assisting with data mining, engineering, application, and more. A data analyst should be proficient in at least one of these languages.
- MATLAB. A programming language and multi-paradigm numerical computing environment, MATLAB is the final step in advanced data plotting, manipulation, and organization. It’s great for companies interested in Big Data and powerful in machine learning. Machine learning is an in-demand field, and having a good grasp of its models can put you ahead.
Learn more about what a data analyst does here.
How Can Springboard Help You Become a Data Analyst?
Springboard’s Data Analytics Career Track builds technical and business thinking skills. Every student is matched 1:1 with a mentor, who is on hand to answer questions, help with curriculum guidance, and help make your transition to data analytics as smooth as possible. With project-based learning, access to industry experts, and a cutting-edge curriculum, you’ll finish Springboard's data analytics bootcamp with every key needed to unlock your next role career move.
Data Analyst Career FAQs
Below you'll find a number of commonly asked questions and answers about becoming a data analyst.
How long does it take to become a data analyst?
With the right education, you could become a data analyst right out of college. If you didn’t major in a related field, no sweat! All the resources are out there. You could develop a great grasp of SQL, Microsoft Excel, and other languages in less than a month with various courses and just exploring the interface. If you’re committed, your career as a data analyst could be right around the corner.
What do you need to study to be a data analyst?
The most common first step is receiving your bachelor’s degree in a relevant field such as computer science, statistical analysis, or mathematics. Subjects to study include linear algebra, statistics, and probability, information management, business information systems, finance, or economics.
Do data analysts need to be good at math?
The short answer is yes. Mathematical thinking and understanding are crucial to being able to effectively manipulate data and communicate different trends, patterns, and relationships. If math is not your forte, the good news is it’s a learned skill. Consider taking different courses in related fields to develop your mathematical thinking.
Coding is not necessarily a required skill for a data analyst. While a surface level understanding is very helpful in processing the programming languages, coding is not a typical task for a data analyst. However, there are certain organizations that include coding in data analysts’ responsibilities.
Is data analytics the right career for you?
Springboard offers a comprehensive data analytics bootcamp. Our data analytics curriculum goes beyond just technical skills to focus on areas where employers find the biggest gaps: strategic thinking, problem-solving, and communication. Watch videos from Microsoft. Learn insights from McKinsey experts. Tackle case studies from Harvard Business School. No other data analytics bootcamp does this. You’ll graduate with an analytical mindset. That’s an edge not just for your job search, but throughout your career.
Check out Springboard’s Data Analytics Career Track to see if you qualify.