BCOR 2205 Information Management Quiz 1 Questions & Answers Already Passed!!

information management - application of management techniques to collect information, communicate it within and outside the organization, and process it to enable managers to make quicker and better decisions why machine learning? - allows for quicker and better decisions machine learning - the science of getting computers to learn without being explicitly programmed (subset of ai) artificial intelligence (ai) - collection of machine learning algorithms with a central unit deciding which of the ml algorithms need to kick in at what time word birth - the first time a baby/toddler says a word data - unorganized facts that need to be processed (raw data; unprocessed data) alphanumeric data - numbers and letters text data - sentences and paragraphs used in written communication image data - graphics, shapes, figures audio - human voice and other sounds information - knowledge communicated or received concerning a particular fact or circumstance (created from data)analysis gap - the large gap between data businesses collect and the information that decision makers require structured data - data that can be stored in a table or database unstructured data - data that does not reside in fixed locations data warehouse - collection of data from different information systems dirty data - duplicate, incorrect, or missing data querying tools - easy to use software allowing users to get specific information from a database reporting tools - often bundled with query tools - present query output in meaningful, understandable formats big data - everything we do is leaving a trace (data) which is analyzable variety (big data) - manage the complexity of multiple relational and non-relational data types and schemas velocity (big data) - streaming data and large volume data movement volume (big data) - scale from terabytes to zettabytes deep learning - has networks that are capable of learning unsupervised from data that is unstructured or unlabeled; inspired by the human brain (subset of ai and ml)supervised data (ml) - data scientist tells the machine what it wants it to learn unsupervised data (ml) - machine determines what to learn/what is important