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Data engineering. Data engineering refers to the building of systems to enable the collection and usage of data. This data is usually used to enable subsequent analysis and data science, which often involves machine learning. [1][2] Making the data usable usually involves substantial compute and storage, as well as data processing.
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...
A United States data item description (DID) is a completed document defining the data deliverables required of a United States Department of Defense contractor. [1] A DID specifically defines the data content, format, and intended use of the data with a primary objective of achieving standardization objectives by the U.S. Department of Defense.
A software design description (a.k.a. software design document or SDD; just design document; also Software Design Specification) is a representation of a software design that is to be used for recording design information, addressing various design concerns, and communicating that information to the design’s stakeholders.
Responsibility assignment matrix. In business and project management, a responsibility assignment matrix[1] (RAM), also known as RACI matrix[2] (/ ˈreɪsi /) or linear responsibility chart[3] (LRC), is a model that describes the participation by various roles in completing tasks or deliverables [4] for a project or business process.
Data science is an interdisciplinary field [10] focused on extracting knowledge from typically large data sets and applying the knowledge and insights from that data to solve problems in a wide range of application domains. The field encompasses preparing data for analysis, formulating data science problems, analyzing data, developing data ...
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