Storytelling with Data- Data Visualization and Customer Complaint Tracking & Analysis (CCTA) Case Study - Statistics Assignment Help

Assignment Task

Assignment 1

Any answer must not exceed beyond a 2-Page limit.

1. Why data visualization matters? What are some of the best practices that you would like to recommend while telling a story with data?
2. What do you mean my misleading visualization? Please explain with an example.
3. Briefly explain univariate, bivariate and multivariate analysis? What are some of the plots or charts that are best suited for data visualization for bivariate analysis?
4. Briefly explain the data visualization process (the steps to be performed for storyboarding and storytelling with data)?
5. What do you mean by the following terms: motive, metrics, manageable data (metadata, master data, dimensions, measures, transactional data), meaningful insights, in a context of storytelling with data (data visualization)?

Assignment 2: Case Study: Customer Complaint Tracking & Analysis (CCTA)

1. Background
2. To analyze a bank customer demographic across geographical locations between nation states, you can download the customer dataset from Super Data Science website under section 6. The spreadsheet has 4,014 rows include the attributes of Customer ID, Name, Surname, Gender, Age, Region, Job Classification, Date Joined, and Balance.
3. Create a dashboard that analyzes customer segmentation (and provides answers to the questions listed below) based on data provided, using Tableau or Jupiter Notebook (Python) based on your choice.
4. Business Challenges
5. Which age group has most of the savings/ balance with the bank?
6. Which are the top 5 regions in terms of total number of customers in a bank?
7. Which are the top 5 regions in terms of total balance of customers in a bank?
8. Which all regions, consists of larger number of male customers than the female?
9. How many customers does the bank have by each of the job classification?
10. Which is the wealthiest segment based on the job classification?
11. Compare the balance of newly joined customers (10%) with the oldest customers (10%)?
12. Who are the most valuable customers (10%) by job and gender across the regions?
13. What is the gap (in terms of average balance) between various regions?

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