ANL203: The Green Mark, a Building and Construction Authority of Singapore rating system: Analytics for Decision-Making Assignment, SUSS, Singapore

Question 1

The Green Mark, a Building and Construction Authority of Singapore rating system, is used to assess infrastructure assets’ environmental friendliness and acknowledge projects employing advanced sustainability strategies. The assessment process includes design and documentation reviews as well as site verifications, culminating in a point-based certification.

Depending on the point scoring, projects can be awarded one out of four Green Mark Ratings (Certified – Gold – Gold Plus – Platinum). The dataset “Building_TMA.xlsx” records the building energy performance in Singapore, containing data fields such as the building address, type, green mark status and rating, size, area, energy use intensity and intensity growth. Note that green marking rating is denoted as “A” if green mark status is “No”.

(a) Identify a business problem that can be addressed through an analysis of the dataset. Provide a clear description of the pertinent data fields and how these fields can be utilized to address the business question. (Maximum of 150 words for part (a))

(b) Generate a summary of the whole dataset in tabular format. You should include the classification of each data field as nominal, ordinal, interval, or ratio. Examine individual variables within the dataset and compute relevant summary measures when applicable. (Up to 200 words for part (b))

(c) Address the data issues and errors in the dataset with explanations and justifications. Illustrate the data preparation with relevant example screenshot(s). (Up to 200 words for part (c))

(d) Employ two (2) graphical charts and one (1) pivot table to present the key features of the data variables or to analyse the relationship among the variables. Please provide a screenshot of each produced chart and pivot table. In your explanation, describe the process of creating the charts and the pivot table and discuss why these visualizations are recommended. (Up to 250 words for part (d))