What Is Data Science? Definition, Examples, and Degree Requirements

What is data science? Data science is an interdisciplinary field focused on extracting insights from data by integrating statistics, programming, and domain knowledge. Data science uses those three skills to collect data, clean it, model it with statistics and machine learning, and turn the result into a decision someone can act on. The U.S. Bureau of Labor Statistics gives a matching data science definition: "Data scientists use analytical tools and techniques to extract meaningful insights from data."

Data science is also one of the fastest-growing fields of work. BLS counts 275,600 data scientist jobs in 2025 and projects 35% growth from 2025 to 2035, against 3% for all occupations.

What Is the Definition of Data Science?

The data science definition has four parts: data science is the use of statistics, programming, machine learning and domain knowledge to extract insights and predictions from data. Each part of the data science definition does a different job, and the definition of data science used by the Bureau of Labor Statistics, extracting "meaningful insights from data", covers all four.

Statistics supplies probability, hypothesis testing and inference, so a finding can be defended as more than a coincidence.
Programming, mostly in Python, R and SQL, handles data at a scale no spreadsheet can.
Machine learning builds models that predict outcomes and recognize patterns automatically.
Domain knowledge tells the data scientist which questions matter and whether an answer makes sense in the real world.

Remove any one of the four and the result is a different field: statistics without programming is classical statistics, and programming without statistics is software engineering.

What Is Data Science About?

Data science is about turning raw data into decisions, and it follows a five-stage lifecycle: collect, clean, analyze and model, visualize, and deploy. What data science is about, in practice, is moving data through those five stages until it changes what someone does.

Pull raw data from databases, sensors, APIs and logs.
Fix errors, fill or flag missing values and standardize formats. This stage takes more time than any other.
Analyze and model. Test hypotheses and train machine learning models on the clean data.
Present the result in charts and dashboards a decision-maker can read.
Put the model into a live system so it keeps producing predictions.

What Is the Primary Goal of Data Science?

The primary goal of data science is better decisions: data science exists to replace guesswork with evidence. The Bureau of Labor Statistics ties the field's growth directly to that goal, noting that "Employment growth for data scientists is expected to stem from an increased demand for data-driven decisions." That demand is behind the 35% projected growth in data scientist jobs from 2025 to 2035.

The primary goal of data science shows up in two kinds of output. Descriptive work explains what happened and why. Predictive work estimates what will happen next, so an organization can act before it does.

What Is a Data Scientist?

A data scientist is a professional who uses statistics, programming and machine learning to extract insights and predictions from data, and then explains those findings to the people who act on them. What is a data scientist's typical background? BLS says data scientists typically need at least a bachelor's degree in mathematics, statistics, computer science or a related field, and it reports a $120,230 median wage for the occupation (May 2025).

A data scientist's week usually includes four tasks: gathering data, exploring it for trends and outliers, building and testing models, and presenting the result. The full picture of data science jobs, pay and outlook is covered in the South Dakota Mines guide to careers in data science.

What Field of Study Is Data Science?

Data science is a field of study that sits at the intersection of mathematics, statistics and computer science. The Bureau of Labor Statistics lists those same three as the typical degree fields for data scientists. What field of study data science belongs to varies by university: at South Dakota Mines, data science is an engineering degree, taught in the Department of Electrical Engineering and Computer Science.

Most data science degrees share a core of calculus, linear algebra, probability and statistics, programming and databases, then add machine learning and data visualization.

What Industry Is Data Science?

What industry is data science in? Data science is a function used inside almost every industry, and the Bureau of Labor Statistics shows which industry data science concentrates in: publishing, broadcasting and content providers employ 12% of data scientists, and computer systems design, corporate management and insurance carriers employ 10% each. Banks and lenders add another 6%.

Outside those five, data science runs inside healthcare systems, manufacturers, energy utilities, agriculture, mining and government agencies.

How Does Data Science Show Up in Your Life?

Data science shows up in your life every time a system predicts something for you: the weather forecast, a streaming recommendation, a fraud alert on your bank card, or a map app's arrival time. The weather forecast is the clearest example of how data science shows up in your life. NOAA reports that a five-day forecast can accurately predict the weather approximately 90 percent of the time, and a seven-day forecast about 80 percent, because models built on satellite and sensor data keep improving.

More everyday examples of data science:

Streaming and shopping services predict what you will watch or buy from what you did before.
Fraud detection. Card networks score each transaction and block the ones that look unlike your history.
Map apps combine live traffic data to estimate when you will arrive.
Hospitals use models to flag patients at risk of complications.

How Is Data Science Used in Mining?

Data science in mining turns equipment and geology data into safer, cheaper extraction: models predict equipment failures from sensor data, estimate ore grade between drill holes, and drive autonomous haul trucks. Caterpillar reported in 2021 that its autonomous trucks running Cat MineStar Command had hauled more than 3 billion tonnes at 17 mine locations, an operation that depends on data science at every step.

Data science in mining is a natural fit for South Dakota Mines, which runs a dedicated Department of Mining Engineering and Management alongside its data science program. Class of 2025 Mining Engineering & Management graduates placed at 100%⁴.

What Is a Data Science Degree?

A data science degree is a bachelor's or graduate program that teaches statistics, programming, machine learning and data management together. What is a data science degree at South Dakota Mines? It is the Data Science & Engineering BS, a 120-credit degree that combines computer science, statistics, mathematics and real-world problem solving, with featured courses in Introduction to Data Science, Data Engineering, Machine Learning and Computers in Society⁵.

The degree is pursuing accreditation from the Engineering Accreditation Commission of ABET. Its data engineering course is the part most data science programs leave out: building the pipelines that collect, clean and serve data at scale.

What Are the Data Science Degree Requirements?

The data science degree requirements at South Dakota Mines are 120 credits for the Data Science & Engineering BS, typically four years of full-time study, and 72 credits for the Data Science & Engineering PhD⁵. Admission to the bachelor's degree follows standard South Dakota Mines undergraduate admission, so strong high school mathematics is the best preparation.

Data science degree requirements at South Dakota Mines

Requirement	Data Science & Engineering BS	Data Science & Engineering PhD
Total credits	120	72 (36 course, 36 research)
Prior degree	High school diploma	Bachelor's in electrical engineering, computer science or engineering, industrial engineering, or mathematics
Minimum GPA	Standard undergraduate admission	3.0 on a 4.0 scale
Application deadline	Undergraduate admissions calendar	February 1 (fall), August 1 (spring)
GRE	Not applicable	Not required
Accreditation	Pursuing ABET (EAC)	Not applicable

PhD eligibility criteria are not strict thresholds; the program considers work and research experience, and PhD students are eligible for assistantships.

Studying Data Science at South Dakota Mines

South Dakota Mines teaches data science as engineering in the Department of Electrical Engineering and Computer Science, from the 120-credit Data Science & Engineering BS through the Data Science & Engineering PhD⁵. Faculty research spans artificial intelligence and machine learning, environmental and geospatial data, human and social data, health and biomedical applications, and advanced manufacturing and immersive technology.

Where graduates go. Data science and engineering students have been hired by Google, Amazon Web Services, NASA, John Deere and GE HealthCare. Across all programs, the 2024-2025 First Destination Report puts South Dakota Mines at 94% placement, a $76,805 average starting salary, and 192 employers in 36 states⁴.

Students engage in hands-on projects and capstone experiences, and build résumés through research and internships. Classes are small enough that faculty know students by name, on a campus in Rapid City, South Dakota, in the Black Hills.

Explore the Data Science & Engineering BS program page.

Frequently Asked Questions

Q: Is data science hard to learn?

Data science is demanding because it combines three subjects: statistics, programming and a domain. Most bachelor's programs, including the 120-credit degree at South Dakota Mines, build all three over four years, starting with calculus, statistics and introductory programming⁵.

Q: What is the difference between data science and computer science?

Data science focuses on extracting insights from data through statistics and machine learning, while computer science focuses on building software systems and understanding computation. South Dakota Mines covers the full comparison in its guide to computer science vs data science.

Q: What programming languages are used in data science?

Python, R and SQL are the core languages of data science. Python dominates machine learning, R remains common in statistics, and SQL is required for pulling data from databases.

Q: Do you need a degree to become a data scientist?

Usually, yes. The Bureau of Labor Statistics lists a bachelor's degree as the typical entry-level education for data scientists, in mathematics, statistics, computer science or a related field.

Q: Is data science a good major?

Yes, on the current numbers. BLS projects 35% growth in data scientist jobs from 2025 to 2035 at a $120,230 median wage (May 2025), and South Dakota Mines graduates across all majors placed at 94% in the Class of 2025⁴.

Q: Does South Dakota Mines have a data science PhD?

Yes. The Data Science & Engineering PhD requires 72 credits (36 course and 36 research), a bachelor's degree with a 3.0 GPA, and an application by February 1 for fall or August 1 for spring. GRE scores are not required.