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Large volumes of data on practically every element of a company's operations and finances are available nowadays. Those who can transform this data into usable, actionable intelligence are highly valued in every business. This course will broaden your understanding of several business analytics approaches that may be used to aid decision-making.
You'll look at descriptive analytics, inferential analytics, and predictive business analytics, building on what you learned in your basic business statistics class. You'll practise data exploration, probability analysis, decision-making under uncertainty, statistical inference, regression analysis, and time-series forecasting. The principles of optimisation modelling and data mining will also be covered. You will utilise a software environment that is appropriate for this unit throughout.
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When a firm decides to use business analytics, it is typically based on the company's or business's end goal. Whatever technique the organisation employs, the final result will be an actionable insight. All of the components or processes that go into business analytics and are utilised to arrive at the findings are listed below.
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The essential business analysis elements are value, need, content, change, solution and stakeholder.
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A systematic research approach to ensure no research gaps and a clear and comprehensive overview.
Get the industry-specific insights for a subject and add more value to research by adding your perspective to it.
Know how to follow the university requirements and marking rubrics. Share all assignment related issues with experts and get instant solutions.
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