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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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