Question
YY company is considering opening a restaurant chain, and you have been asked to evaluate whether it would be a worthwhile investment. Therefore, you have
YY company is considering opening a restaurant chain, and you have been asked to evaluate whether it would be a worthwhile investment. Therefore, you have decided to perform a study on the available dataset to demonstrate the viability of the task. Requirements:
use Power Bi to make this and ss the result
1. Follow the CRoss Industry Standard Process for Data Mining (CRISPDM) model1 as the basis for the case study.
a. Business Understanding
b. Data Understanding
c. Data Preparation
d. Data Modeling
e. Evaluation
f. Deployment
2. Search and acquire a customer sales dataset from a public data source that offers information on customer purchases such as product name, price, quantity, date, and customer ID. You may also want to collect additional data on customer demographics, such as age, gender, and location.
give the link data u found
3. Clean the data to ensure accuracy and consistency. This may involve removing duplicates, correcting errors, and filling in missing values.
4. Explore the data to gain a better understanding of the customer behavior and sales trends. This may involve creating visualizations and calculating summary statistics such as average purchase amount, frequency of purchases, and top-selling products.
5. Use techniques such as clustering techniques to segment customers based on their behavior and demographics. This will help identify different customer groups and their purchasing patterns.
6. Use techniques such as time-series analysis to forecast future sales for the company. This will involve analyzing past sales trends and seasonality, as well as external factors such as economic indicators and promotional campaigns.
7. Based on the analysis, provide insights and recommendations to the retail company on how to improve sales and customer satisfaction. This may involve suggesting targeted marketing campaigns, improving product recommendations, or optimizing pricing strategies.
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