MBAS901 Assessment Answers Australia

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Are you studying MBAS901 Essential Elements for Business Analytics course? If yes, then we have a piece of good news for you. In Australia, there are a lot of opportunities for business analysts. The demand for business analysts in Australia is among the greatest in the world. According to a survey published in Onya Magazine, Australia's number of business analyst positions will increase to 26,100 by 2023.

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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.

What are the Learning Outcomes of this Course?

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• Learn how and why data gathering and analysis may help you better understand your customers, users, and/or stakeholders and how they engage with your company's goods and services.
• Learn and practise ways for finding, preparing, and analysing data to increase your capacity to create more accurate predictions that result in positive business results.
• Improve your capacity to discuss business analytics project outcomes.
• Examine the function of business analytics in assisting decision-making in today's organisations;
• comprehend and evaluate various business analytics methodologies, as well as their application to a range of decision-making needs in various situations; and
• apply and assess relevant statistical techniques and software for data analysis to aid corporate decision-making.

Important Elements of Business Analytics

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.

• Data mining - Using machine learning, database systems, and statistics, it is an approach for sifting through large volumes of data to identify patterns, trends, and other information about data that isn't apparent.
• Text mining - It is a method of extracting high-quality data or information from texts or communications in online applications or on the Internet.
• Aggregation of Data - First, the data is acquired, and then it is given in a summary style. The data is usually consolidated, cleansed, and filtered once it is collected to reduce errors and redundancies.
• Predictions - While business analytics is used to assess a process that occurred over a period of time or season, firms may estimate future occurrences or behaviour using historical data.
• Visualisation of Data - One of the most significant aspects of business analytics is data visualisation. It simply takes the data's facts and insights and displays them in an interactive graph or chart. This procedure aids in the real-time tracking of company indicators and KPIs to have a better knowledge of performance and goals.

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Study Materials for Completing the Course

• Palepu, Krishna G., Paul M. Healy, Sue Wright, Michael Bradbury, and Jeff Coulton. Business analysis and valuation: Using financial statements. Cengage AU, 2020.
• Asif, Zaheeruddin. "Integrating the supply chain with RFID: A technical and business analysis." Communications of the Association for Information Systems 15, no. 1 (2005): 24.
• Hart, Peter Edward, and Sigbert Jon Prais. "The analysis of business concentration: a statistical approach." Journal of the Royal Statistical Society. Series A (General) 119, no. 2 (1956): 150-191.
• Fleisher, Craig S., and Babette E. Bensoussan. Business and competitive analysis: effective application of new and classic methods. FT Press, 2015.
• Cadle, James, Debra Paul, and Paul Turner. Business analysis techniques: 72 essential tools for success. BCS, The Chartered Institute, 2010.
• Rosemann, Michael, and Jan vom Brocke. "The six core elements of business process management." In Handbook on business process management 1, pp. 105-122. Springer, Berlin, Heidelberg, 2015.
• Reinsel, Gregory C. Elements of multivariate time series analysis. Springer Science & Business Media, 1997.
• Brajer-Marczak, Renata. "Elements of knowledge management in the improvement of business processes." Management 20, no. 2 (2016).

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