MGT782 Managerial Business Analytics Assignment Answers Malaysia

MGT782 Managerial Business Analytics is an online course that covers the concepts and tools of business analytics and their application to businesses. The course covers topics such as data collection, analysis, and interpretation; predictive modeling; and optimization techniques. Students will learn how to use analytics to make better decisions in areas such as marketing, operations, and human resources. The course also provides a foundation for further study in data science and machine learning. Through real-world examples and hands-on exercises, students will gain a practical understanding of how business analytics can be used to improve decision-making in businesses.

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In this section, we are discussing some assigned tasks. These are:

Assignment Task 1: Apply appropriate data analytics tools and models to solve business decision-making problems.

Data analytics is the process of examining data sets in order to draw conclusions about the information they contain. Data analytics tools and models can be used to solve business decision-making problems by identifying trends, patterns, and relationships.

There are a variety of data analytics tools and models that can be used to solve business decision-making problems. Some of the most common data analytics tools and models include:

• Descriptive analytics: Descriptive analytics tools and models are used to describe data sets. They can be used to summarize data sets, identify trends, and find patterns.
• Predictive analytics: Predictive analytics tools and models are used to predict future events. They can be used to identify trends and patterns and make predictions about what will happen in the future.
• Prescriptive analytics: Prescriptive analytics tools and models are used to prescribe actions. They can be used to recommend solutions to problems and make decisions about what should be done in the future.

These are just a few of the many data analytics tools and models that can be used to solve business decision-making problems.

Assignment Task 2: Explore how data is created, stored, accessed, and processed in the industrial 4.0 business world.

The industrial 4.0 business world is a data-driven environment. Data is created, stored, accessed, and processed in the industrial 4.0 business world in order to make decisions and take action.

• Data creation: Data is created in the industrial 4.0 business world through sensors, devices, and applications.
• Data storage: Data is stored in the industrial 4.0 business world in databases, data warehouses, and data lakes.
• Data access: Data is accessed in the industrial 4.0 business world through APIs, query languages, and BI tools.
• Data processing: Data is processed in the industrial 4.0 business world through ETL, data mining, and machine learning.

These are just a few of the many ways in which data is created, stored, accessed, and processed in the industrial 4.0 business world.

Assignment Task 3: Communicate data analytics results to stakeholders to justify and support business decisions.

Data analytics results must be communicated to stakeholders in order to justify and support business decisions. Data analytics results can be communicated through reports, presentations, dashboards, and data visualizations.

When communicating data analytics results, it is important to consider the audience and the purpose of the communication. The audience will determine the level of detail and the type of information that is communicated. The purpose of the communication will determine the format and delivery method.

Some tips for communicating data analytics results:

• Consider the audience: Who will be receiving the communication? What do they need to know?
• Determine the purpose: Why are you communicating the results? What decision needs to be made?
• Choose the format: What is the best way to communicate the results? Reports, presentations, dashboards, or data visualizations?
• Delivery method: How will you deliver the results? In-person, by email, or by posting it online?

When communicating data analytics results, it is important to be clear, concise, and accurate. The results should be presented in a way that is easy to understand and actionable.

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