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Data science process flowchart from Doing Data Science, by Schutt & O'Neil (2013) Analysis refers to dividing a whole into its separate components for individual examination. [10] Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1]
For example, a data analyst might analyze sales data to identify trends in customer behavior and make recommendations for marketing strategies. [37] Data science, on the other hand, is a more complex and iterative process that involves working with larger, more complex datasets that often require advanced computational
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Responsibilities include experimental design, data processing, and analysis. Senior Analyst: Participates in the development of projects and directs the operational execution of the assigned projects. Works closely with the analyst, junior analyst, and other personnel in developing the research design and data collection. Prepares the final report.
R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.
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