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The CGMA Competency Framework was also launched in 2014. The framework shows the range of technical, accounting and finance skills that management accountants need to do their jobs and consists of four knowledge areas: Technical Skills, Business Skills, People Skills and Leadership Skills, all underpinned by Ethics, Integrity and Professionalism.
The qualification is structured in three modules, plus an Ethics and Professional Skills module and a Professional Experience Requirement (PER). [12] The Applied Knowledge level consists of 3 examinations: BT - Business and Technology; MA - Management Accounting; FA - Financial Accounting; The Applied Skills level consists of 6 examinations:
The Uniform Certified Public Accountant Examination (CPA Exam) is the examination administered to people who wish to become Certified Public Accountants in The United States of America. The CPA Exam is used by the regulatory bodies of all fifty states plus the District of Columbia , Guam , Puerto Rico , the U.S. Virgin Islands and the Northern ...
This maturity model is prescriptive in the sense that the model consists of four distinct phases that each plot a path towards big data maturity. Phases are: Phase 1, undergo big data education; Phase 2, assess big data readiness; Phase 3, pinpoint a killer big data use case; Phase 4, structure a big data proof-of-concept project [11]
It is a tool to discover and decipher useful information for business decision-making. It is imperative in inferring information from data and adhering to a conclusion or decision from that data. Data analysis can stem from past or future data. Data analysis is an analytical skill, commonly adopted in business, as it allows organisations to ...
software.intel.com /content /www /us /en /develop /tools /data-analytics-acceleration-library.html oneAPI Data Analytics Library (oneDAL; formerly Intel Data Analytics Acceleration Library or Intel DAAL), is a library of optimized algorithmic building blocks for data analysis stages most commonly associated with solving Big Data problems.
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Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. [2] In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. [3]
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