Data Theory vs Data Science: What's the difference?

I'm interested in pursuing a career in the data field but I'm a bit confused about the differences between data theory and data science. Could someone please elaborate on the main differences and which one might be more suitable to pursue in college? Thanks!

The main difference between data theory and data science lies in their scope and focus. Data theory is the more fundamental and mathematical side of the data field, while data science is an applied discipline that uses the concepts and techniques from data theory in real-world problem-solving scenarios. Let's dive deeper into both fields:

1. Data Theory: This field is concerned with the mathematical and statistical foundations of data collection, analysis, and interpretation. It involves studying concepts such as probability theory, statistical inference, signal processing, information theory, and optimization. Pursuing data theory in college will provide you with a strong theoretical background and may lead you to a research-oriented career, or into more specialized fields like mathematical modeling, machine learning, or algorithm design.

2. Data Science: This is an interdisciplinary field that focuses on extracting insights, patterns, and useful information from large datasets using a combination of domain expertise, programming skills, and statistical techniques. Data scientists use knowledge from data theory to apply various tools, algorithms, and machine learning methods to analyze real-world data and make data-driven decisions. Pursuing data science in college will expose you to skills such as data visualization, data cleaning, and programming languages like Python and R. A degree in data science can lead you to careers in industries like healthcare, finance, marketing, and more.

To determine which field is more suitable for you, consider your interests and career goals. If you enjoy diving deep into the mathematical and theoretical aspects of data and potentially want to pursue research or academia, data theory may be more suitable for you. On the other hand, if you prefer working on practical problems and would like to develop a versatile skillset applicable to various industries, data science may be a better fit.

You can also explore courses and internships in both fields, as well as discuss the differences in more detail with professors who specialize in each area, during your college years to help you refine your interests and make an informed decision. Additionally, many colleges offer degrees in data science that include foundational data theory courses, and vice versa, so you may have the opportunity to study aspects of both fields as part of one program.

Good luck with pursuing your interest in data!