MGT555 Business Analytics Assignment Sample UiTM Malaysia

The course provides students with an introduction to the field of business analytics, which has been defined as the extensive use of data. It is discussed in-depth through statistical and quantitative analysis; descriptive models that can be used for prediction or prevention purposes; predictive ones where predictions are made based on previous observations related to customer behaviour patterns (e.g., what they buy). Finally, there are prescriptive modelling techniques such as recommendation engines using machine learning algorithms. Students will also receive an introduction to some of the software used in business analytics.

The course is structured around a series of lectures, case studies, and labs. The lectures will provide the necessary theoretical background for the concepts covered in the course. The case studies will allow students to see how these concepts are applied in practice. And the labs will allow students to work with the software used in business analytics so that they can get a hands-on understanding of how it works.

By the end of the course, students should have a good understanding of the basics of business analytics and be able to apply some of the methods learned in the course to real-world data sets. This course is aimed at students who have an interest in using data to improve business decision-making. It will be of particular interest to students who are considering a career in business analytics or data science. However, no prior knowledge of business analytics or data science is assumed.

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Assignment Activity 1: Demonstrate managerial skills in a data-driven business environment.

In a data-driven business environment, managers need to have strong data analysis skills. They need to be able to understand and interpret data, identify trends and patterns, and make recommendations based on their findings.

Good managerial skills in a data-driven business environment involve the following:

  1. Strong analytical skills: The ability to understand and interpret data is critical for managers in a data-driven business environment. They need to be able to identify trends and patterns and make recommendations based on their findings.
  2. effective communication: To share their findings with other members of the organization, managers need to be able to communicate effectively both verbally and in writing.
  3. presentation skills: The ability to present data clearly and concisely is another important skill for managers in a data-driven business environment.

Assignment Activity 2: Apply the theories, concepts and applications of business analytics in supporting managerial decisions.

Business analytics can be used in several ways to support managerial decisions. Predictive modelling, for example, can be used to identify patterns in data that can then be used to predict future outcomes. This information can help managers make informed decisions about things like inventory levels, production planning, and future marketing strategies.

Data mining can also be used to reveal relationships between different data points. This information can help managers understand how various factors (such as price changes or customer satisfaction) impact their business. And decision trees can help managers visualize the possible outcomes of different choices so they can make more informed decisions.

All of these techniques and more are available to managers through business analytics software programs. By using these tools, managers can make better decisions that lead to improved business performance.

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Assignment Activity 3: Display skills in using Tableau software and Microsoft Excel in data visualization and analysis.

There are many skills that you can display when using Tableau software and Microsoft Excel in data visualization and analysis. Perhaps the most important skill is the ability to effectively communicate data-driven insights to your audience. To do this, you need to be able to not only produce informative and visually appealing charts and graphs but also be able to explain how the data was gathered and what it means clearly and concisely.

Other skills that are important when using Tableau and Excel for data visualization include the ability to filter, sort and perform calculations on data sets. Being able to tell a story with data – whether it’s identifying trends, outliers or patterns – is also an extremely valuable skill. And of course, having a strong foundation in basic statistical concepts is also important for effectively analyzing data. If you can display these skills when using Tableau and Excel for data visualization, you will be well on your way to becoming a proficient data analyst.

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