PART A: CASE STUDY Read the case below. Answer the following TWO (2) questions. A construction manager for company Andaman has been engaged to develop a customized customer solutions. The construction manager intends to develop data analytics to present his project performance. He wanted to indicate the project gantt, the estimated revenue by consultants, the budget expenditure variance and customer satisfaction. He has painstaking summarize the performance as indicated in Table 1 (data is available on the reference below). Based on the information (from Table 1) he intends to develop a performance dashboard to show the project performance with a crisp management report. Table 1: Project Performance Summary In addition, there is a new opportunity arise for the second half of the year. There is opportunity Andaman Sdn Bhd. to expand business to construct a new warehouse for an existing e-commerce company. The are two options. The first option is expand at site A and the other option is to expand at site B. Both site A and B offer different payoff with different level of investment. The company can either expand at site A (RM6 million construction cost) OR site B (RM10 million construction cost). The project manager wanted to evaluate the options for a project (new warehouse) expansion objectively based on the expected monetary value (EMV). a) As a consultant, explain to the construction manager the benefits of using a decision tree to determine EMV. [10 marks] b) Based on this scenario (draw a decision tree with EMV), state your recommendation to the construction manager. [20 marks] Question 3 Businesses leverage on artificial intelligence to understand customer patterns, behaviors in depth and to predict some business actions. Machine learning is a component of artificial intelligence to comprehend big data, characteristics, building methods and associate relationship within the massive data structure. Data analysis acquired through machine learning. Machine learning algorithms build a model based on sample data, known as training data, to make predictions or decisions without being explicitly programmed to do so. This has been used in the filed of medicine, logistic, marketing, manufacturing, agriculture just to name a few. (a) Explain the differences between training dataset and testing dataset, and why they are important in the cross-validation process. [10 Marks] c) Based on typical scenario in your workplace or business, identify OPPORTUNITY where you can use data analytics to improve operations, business, or process. Explain the current problem and how data analytics, and the manner data visualization assist in solving problems