Analysis of Customer Reviews on a Womens Clothing E-Commerce Dataset

Dataset Overview

Question 1This 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-reviewsThe 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 (Womens Clothing E-Commerce Reviews.csv). Each row of the dataset corresponds to a customer review. The variables and descriptions are:Column NameDescriptionClothing IDInteger Categorical variable that refers to the specific piece being reviewedAgePositive Integer variable of the reviewers ageTitleString variable for the title of the reviewReview TextString variable for the review bodyRatingPositive Ordinal Integer variable for the product score granted by the customer from 1 Worst, to 5 BestRecommended INDBinary variable stating where the customer recommends the product where 1 is recommended, 0 is not recommendedPositive Feedback CountPositive Integer documenting the number of other customers who found this review positiveDivision NameCategorical name of the product high level divisionDepartment NameCategorical name of the product department nameClass NameCategorical name of the product class name(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 non-textual data in the given dataset. Explain the critical steps to ensure successful applicatiUniversity of Social Sciences (SUSS)Page 6 of 7 ECA – January Semester 2021of 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 textmining in order to understand the customers better. Identifyfive (5)challenges when analyzing the given textual data. State the solutions that can be applied to address the each of challenges identified.