Information retrieval describes the scientific methods, processes, and procedures that are used in the retrieval of recorded data in files and databases. This science covers the overall search activity that seeks information in a document (including text and images), the document itself, or the metadata within a document. This type of unstructured material (often in text-based documents) is usually found in full-text databases. Many modern libraries and archival storage centers use information retrieval software that serves to organize, store and retrieve data and information from document sites and article repositories. When searching for particular data or information, a user can search for this information using full-text or content-based indexing tools.‎

Information retrieval is valuable to learn because it helps us make sense of information and data. Imagine the difficulty of looking for information on the internet or in a library database without the use of a centralized search mechanism. It would just be a blur of reports, studies, plain text, images, and more. Information retrieval systems serve to bring knowledge and understanding to this information and data. Learning about information retrieval may help you understand the ways that unstructured data is collected, reviewed, and organized, and how data science and knowledge management combine to create a basis for understanding information retrieval.‎

Some of the typical jobs you can get from learning information retrieval could include jobs like a data scientist, data engineer, machine learning engineer, library archivist, database developer, knowledge management director, and similar roles that work with data and information. As more information is classified as data, the careers that are most often seen in the science of information retrieval are centered around data science and its related disciplines.‎