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Data analysis is a systematic method of cleaning, transforming and modelling statistical or logical techniques to describe and evaluate data. [44] Using data analysis as an analytical skill means being able to examine large volumes of data and then identifying trends within the data.
Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]
Business analytics (BA) refers to the skills, technologies, and practices for iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods.
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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 ]
The Knowledge, Skills, and Abilities (KSA) framework, is a series of narrative statements that, along with résumés, determines who the best applicants are when several candidates qualify for a job. The knowledge, skills, and abilities (KSAs) necessary for the successful performance of a position are contained on each job vacancy announcement ...
More specific qualifications may be required additionally: [9] In (senior) financial management roles, a professional accounting certification – the CPA, CA, CMA, or CIMA – is often a prerequisite; this, given the overlap with tax and financial reporting. [26] Risk managers increasingly require the FRM / PRM, or an actuarial qualification ...
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