What do data professionals do?

They do different things. Data are discrete, continuous values that offer insight. They are often found in largely raw and unprocessed collections that are meaningless until something or someone can make sense of what they can reveal. Here's a high level overview of different data professions.

Data analysts: collect, sort, and interpret data to discover patterns and insights to enable decision making.

Skill sets: SQL, Excel, Power BI, Tableau, Statistics and mathematics.
Common projects: Analyze trends and patterns, use low-code software (or programming) to create dynamic dashboards and reports.

Data engineer: Designing, building, and maintaining data pipelines and infrastructure.

Skill sets: Python, big data, ETL tools, cloud platforms.
Common projects: gathering & cleaning data sets, setting up data warehouses and data lakes.

Data scientists: Employ data to build dynamic models and perform forecasts.

Skill sets: R, Python, C/C++, machine learning tools, statistics/mathematics, data visualization.
Common projects: Create machine learning models; generate prescriptive analytics.

Almost everything can either produce or be described by data. The U.S. Bureau of Labor and Statistics forecasts a strong demand for data professionals, with a 36% increase in employment between 2023 to 2033. If you like analytical thinking and have great attention to detail, this could be a great career possibility.