Data Science vs. Data Analytics
Thinkful Virtual Webinar Replay | 9:00pm-10:00pm, 2/20/23
During a recent webinar, I learned that data science is often used in research and development, where complex algorithms and models are used to analyze large amounts of data. Data scientists are typically involved in the design and development of these models, and they may use a variety of programming languages, such as Python, R, and Java.
Data analytics, on the other hand, is often used in the business world to help organizations make data-driven decisions. Data analysts are typically involved in the collection, cleaning, and analysis of data, and they may use tools such as Excel, SQL, and Tableau. While there are similarities between the two fields, there are also important differences in terms of the types of problems they solve and the skills and expertise required to be successful.
As a college student who is interested in these fields, it was very helpful for me to understand the key differences between the two to make the best decisions for developing my career.