MGT555 Business Analytics Assignment UITM Example Malaysia
The business world is one that relies heavily on data-driven decision making. This assignment MGT555 UiTM provides an introduction to the field of analytics, which has been defined as the statistical and quantitative analysis used in conjunction with other descriptive models for predictive purposes or prescriptive modelling – allowing businesses to make smarter decisions about their future prospects by employing various techniques such as machine learning algorithms based off observed patterns within large datasets using Excel & Tableau tools
New learners are encouraged to take this online class since they can actively participate through case studies (presentations) projects while still being taught from instructor-led lectures if needed.
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We also provide you with an assignment for business analyst in different forms such as: MGT555 group project, assignment 2 MGT555, MGT555 individual assignment 1, MGT555 group assignment.
Assignment Task 1: Apply the theories, concept and applications of business analytics
Business analytics is the process of leveraging the advanced computational infrastructure for all types of organizations. One application would be to monitor customer behavior in order to make informed strategic decisions.
Business analytics provides meaningful, timely and logically sound information for management decision making by analyzing data from many sources i.e., on-premise, cloud or public sources, while using databases that are running on commercial off the shelf software suites. The ability to interpret current exposures while anticipating future exposures via predictive modeling will guide an organization through smart economic choices with increased certainty backed by data rather than ambiguity based on assumptions which can lead to erroneous conclusions leading to costly actions that don’t produce success or new opportunities.
Business analytics can be used in a number of ways within a business. Some common applications include customer segmentation, marketing campaign analysis, pricing optimization, fraud detection, and supply chain management.
- Customer segmentation is the process of dividing your customer base into groups based on shared characteristics. This can be done using demographic information, such as age, gender, and income level, or behavioral information, such as past purchase behavior or loyalty status. Once your customer segments have been identified, you can then tailor your marketing messages and offers to appeal to each group.
- Marketing campaign analysis involves evaluating the results of your marketing campaigns to determine whether they were successful. This includes assessing such factors as the number of leads generated, the amount of revenue generated, and the cost-per-acquisition. By analyzing your marketing campaigns in this way, you can identify which ones are most effective and make adjustments to improve future outcomes.
- Pricing optimization is the process of finding the right price for your products and services. This involves analyzing what your competitors are charging, as well as the demand for your products and services. By pricing your offerings in a way that maximizes profits while still remaining competitive, you can improve your bottom line.
- Fraud detection involves monitoring for fraudulent activity within your business. This includes both the schemes perpetrated by outside parties, as well schemes inside your own firm, such as embezzlement or kickbacks. The use of big data analytics can be extremely helpful in this process, allowing you to track everything from sales transactions to website visits to determine whether there is anything unusual or suspicious.
- Supply chain management involves optimizing the flow of goods through your business network. This can be as simple as matching up customer demand with inventory levels, or as complex as managing third-party supplier relationships and compliance requirements for regulatory agencies.
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Assignment Task 2: Display skills in using Tableau software and Microsoft Excel in data visualization and analysis.
Tableau is a software tool designed specifically with data visualization in mind. It is intuitive and easy to learn, making it an easy way for beginners to get started with data visualization. The Tableau dashboard interface allows you to easily join many different types of visualizations together, such as graphs and maps side by side. For companies that need something more than just quickly looking at how certain statistics change over time–such as for analyzing patterns within the expense reports of your employees per month–Tableau has advanced filtering capabilities so users can explore subsets of data and find irregularities or outliers.
Computers are best for doing linear algebra, matrix operations, and other things that humans don’t do well. They’re also good at statistics – another area where human judgement is less accurate than a machine. All of these areas, including data visualization and analysis, represent opportunities for the computer to be used more fully in solving problems.Excel offers many templates displaying skills in using + Microsoft Excel in data visualization and analysis. Templates are currently available on templates called “Charts” which provide step-by-step instructions on how to create charts that visualize or analyze data sets with just a few clicks of the mouse. The step-by-step guide walks you through the data selection process, and how to use Excel’s charting features to quickly create a professional looking visualization or analysis.
There are many different software tools that can be used for data visualization. While some are more specialized, such as Tableau, others are more general purpose. Microsoft Excel is one such tool that can be used for data visualization, as it has a wide variety of features and options that can be used to create professional-looking visualizations. In addition, Excel offers many templates that provide step-by-step instructions on how to create different types of charts, which can be helpful for beginners.
Assignment Task 3: Demonstrate managerial skills in data-driven business environment.
In a data-driven business environment, it’s essential to be able to make sound decisions based on accurate information. As a manager, you must be able to:
- Collect and analyze data in order to identify trends and opportunities
- Use data to make informed decisions about product development and marketing strategy
- Manage a team of analysts who can help you gather and interpret data
- Communicate the findings of your analysis to decision makers in the company
In general, the role of a manager in Data Science is to provide guidance for other team members in an organization. They are also responsible for making sure that the team is doing everything they need to do to complete their work scope(s) / objectives.
Other responsibilities include planning and managing budgets, setting up processes for dealing with operational issues, identifying when new skills are needed within the team, recruiting new people when necessary, and maintaining team morale.
It is important for managers to have good communication and problem-solving skills in order to be successful in this role. They must also be able to work effectively with people from different backgrounds, and be able to manage their time efficiently.
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