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4 paź 2019 · To put data science in context, we present phases of the data life cycle, from data generation to data interpretation. These phases transform raw bits into value for the end user.
9 cze 2020 · In addition, we divide a big data life cycle into five phases (i.e., collection, storage, analytics, utilization, and destruction), and define the security taxonomy of the big data life...
23 cze 2019 · Data science is the study of extracting value from data. “Value” is subject to the interpretation by the end user and “extracting” represents the work done in all phases of the data life cycle (see Figure 1).1. Figure 1. The Data Life Cycle. The cycle starts with the generation of data.
10 lis 2020 · The data life cycle is introduced, together with its stages and the typical data operations for each stage. A classification of datasets into structured, semistructured, and unstructured is discussed, as well as a description of the types of attributes that can be expected for structured datasets.
31 sie 2020 · Different organizations lean to produce high quality frameworks to manage data throughout their lifecycle like the developed architecture for Big Data named NIST Big Data Reference...
1 sty 2023 · Download reference work entry PDF. Definition. Data life cycle, or data management life cycle, refers to the whole procedure of data management, starting from the conceptualization of a research question to creating a data product (Fig. 1). In different scenarios, data life cycle models can vary.
The data life cycle provides a high-level overview of the phases involved in the successful management of big data for its use and reuses [6, 15]. Data lifecycle is helpful to identify dataflows and work processes for stakeholders in the GBDE.
