Any spreadsheet application will work, although Microsoft Excel is the most popular. It might sound strange to mention “data analysis” in a list of required data analyst skills, but analysis as a specific skill is necessary. This data analyst resume demonstrates good examples of leadership and teamwork with bullet points like ‘Managed a cross-functional team’.

Everyone’s path is different, but a common step is typically gaining relevant data science skills and continuing education. In addition to computer science, some data scientists may choose to apply their skills to specific areas of interest to them, such as engineering and natural sciences. To advance their careers, they can dig deeper with an online master’s in data science program. To become a data analyst or data scientist, it may benefit you to obtain at least a bachelor’s degree in a quantitative field such as mathematics, statistics or computer science.

Ready to land a job in data?

SAS is primarily used in the medical industry, whereas SQL is often used for retrieving data from databases. As well as Excel, analysts need to be familiar with at least one querying language. These languages are used to instruct computers to do specific tasks, including many related to the analysis of data. Programming languages such as Python and R also have a wide variety of powerful programs dedicated to analyzing data. Having a thorough grounding in statistics is also beneficial—you can start by learning about descriptive and inferential statistics, and work up from there.

Understanding MATLAB isn’t a needed skill for data analysts, but given its vast range of applications and use, having at least a working knowledge of the environment can help you stand out to companies. Most data analyst jobs listings mention knowledge of SQL as a requirement. Besides being an essential skill, SQL is a great introduction to learning programming languages.

Learning Data Analytics: 1 Foundations

Junior Data Analysts will benefit from a foundational understanding of algorithms, statistics, and the concepts of how machine learning works. Excel is a super useful tool for basic data visualization https://g-markets.net/software-development/working-across-time-zones-pros-cons-and-best/ and some simple manipulation. Strong quantitative skills are therefore an essential part of a data analyst’s toolkit. Of course, the level of understanding may differ based on job requirements.

For example, if you’re working for a company with an online store, you might need to understand the nuances of e-commerce. Written communication is also incredibly important — especially when you’re writing a summary of your analysis or explaining a discovery in your data exploration. Humans are visual creatures — that means Python Developer: Roles & Responsibilities, Skills & Proficiency most people will understand a chart or a graph more quickly than they will understand a spreadsheet. A data analyst will commonly need to retrieve data from one or more sources and prepare it for numerical and categorical analysis. Data cleaning also involves resolving missing and inconsistent data that may affect analysis.