Section A
Question 1
This ECA requires you to analyze a clothing E-Commerce dataset that includes customer reviews. The data is available from the Kaggle website:
https://www.kaggle.com/nicapotato/womens-ecommerce-clothing-reviews
The dataset has been anonymized and the references to the company in the review text and title were replaced with a generic term “retailer”. You are required to download the dataset (Women’s Clothing E-Commerce Reviews.csv). Each row of the dataset corresponds to a customer review. The variables and descriptions are:
(a) Imagine you are tasked to prepare a visualization analysis using the given dataset. Identify one (1) possible business problem that can be addressed by your visualization analysis. Explain how to clean and prepare the dataset in an analyzable form. Explain the benefits and challenges of using the given dataset from the Kaggle website.
(b) Discuss the types of charts that are recommended to address the business problem identified in (a). Produce the charts and the dashboard using Tableau. Explain how your visualization analysis addresses the problem mentioned in Part (a).
(c) Identify the appropriate data mining technique and tools to predict customer sentiment (target outcome – whether the sentiment is positive, negative, or neutral) using the nontextual data in the given dataset. Explain the critical steps to ensure a successful application of the technique and tools to achieve the objective here.
(d) The dataset includes textual data (i.e., review text/title). You would like to apply text mining in order to understand the customers better. Identify five (5) challenges when analyzing the given textual data. State the solutions that can be applied to address the each of challenges identified.
