Assessment Description
In this individual assessment, students will be given an opportunity to evaluate the strategies for data analysis and interpret these results for decision-making. More importantly, students will practise preparing and analysing data-rich reports as a cornerstone of business decision-making and direction using tangible and intangible resources in digital data management. Assessment Instructions
At the end of the week 9 workshop, your workshop facilitator will form the class into groups of 3 to 4 students. Once created, you and your partner will undertake the team inventory questionnaire to understand each other's preferred working styles. Attendance is mandatory so you can a) get acquainted with your partner and b) discuss your team's working style by reviewing the team inventory questionnaire results. Your workshop facilitator will provide further guidance on the day of your scheduled class. During the week 10 workshop, you and your partner must participate in a 90-minute in-class activity to prepare and create a dashboard using one of your preferred business intelligence tools (Power BI, Tableau, Excel, etc.). Let's imagine you and your team working for Kaplan Hotels. Your team would like to improve the hotel's performance by understanding customers' demands. From there, you will forecast the number of guests for the first quarter of 2023. To accomplish that aim, you and your team are required to perform simple data visualisation and analysis. Your workshop facilitator will provide you with the dataset at the start of the activity. Once received, you and the team are required to collaboratively create a dashboard and extract the insights from the dashboard.
Upon the conclusion of the activity, your team must deliver a 6-minute presentation on the following: • How the data preparation process is performed. • The types of visualisation and dashboards chosen. • The summary of the story that the dashboard tells. By the beginning of week 11, individually, you are required to submit 1500-word written data to reflect on your in-class activity and forecasting work. Specifically, your report must include the following: • Summarise the essential findings and story in customer's demands from the dashboard • Summarise the data mining process (Data cleaning, data merge, data selection, data modelling, etc.) • Analyse the data components (time series data components) • Select at least two (2) different forecasting methods to forecast the number of guests coming in the first quarter of 2023. Then, illustrate the forecasting results in plot graphs. • Analyse and compare the forecasting result. Give your evaluations on the forecasting technique. Relevant sources of information should support your justifications and recommendations, and your original work on dashboard and forecasting in BI tools must be demonstrated. These must be referenced in accordance with Kaplan Harvard Referencing Style. Workshop slides, Wikipedia and other 'popular' sites are not to be used.
Please provide answer in 1500 words with text citation and provide at least 8-10 reference