https://github.com/lefteris-souflas/sas-programming-and-machine-learning
Applied SAS techniques for data analysis and machine learning in a milestone project. Base SAS Programming and SAS Viya tools were utilized for preprocessing, customer profiling, sales analysis, promotions, supplier evaluation, and customer segmentation. Results were visualized comprehensively.
https://github.com/lefteris-souflas/sas-programming-and-machine-learning
customer-profiling data-analytics data-exploration market-basket-analysis pre-processing recency-frequency-monetary sas-machine-learning sas-oda sas-programming sas-studio sas-visual-analytics sas-viya
Last synced: 2 months ago
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Applied SAS techniques for data analysis and machine learning in a milestone project. Base SAS Programming and SAS Viya tools were utilized for preprocessing, customer profiling, sales analysis, promotions, supplier evaluation, and customer segmentation. Results were visualized comprehensively.
- Host: GitHub
- URL: https://github.com/lefteris-souflas/sas-programming-and-machine-learning
- Owner: Lefteris-Souflas
- License: mit
- Created: 2024-03-28T20:38:09.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-18T19:34:16.000Z (about 1 year ago)
- Last Synced: 2025-01-12T20:33:36.715Z (4 months ago)
- Topics: customer-profiling, data-analytics, data-exploration, market-basket-analysis, pre-processing, recency-frequency-monetary, sas-machine-learning, sas-oda, sas-programming, sas-studio, sas-visual-analytics, sas-viya
- Language: SAS
- Homepage: https://www.credly.com/badges/3e55ab37-3cf0-4a69-9103-9aa7cfe58b6c/public_url
- Size: 16.1 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Academic Specialization in SAS Programming and Machine Learning
Milestone Project for obtaining the SAS Academic Specialization in SAS Programming and Machine Learning from SAS and AUEB's MSc in Business Analytics
## Milestone Project
### A. Objective of the Project
This Milestone Project is a crucial step toward obtaining the SAS Academic Specialization in SAS Programming and Machine Learning. The project aims to apply techniques for accessing, processing, managing, and mining real-world data to provide solutions to contemporary business problems using Base SAS Programming, SAS Visual Analytics, and SAS Visual Data Mining and Machine Learning on SAS Viya.
### B. Base SAS Programming Using SAS Studio on SAS Viya
1. **Data Pre-processing:**
- Calculate the number of SKUs per invoice and total value of SKUs per invoice.
- Divide invoice observations into sales and returns transactions.
- Calculate customer age and categorize them into age ranges.
2. **Customer Profiling:**
- Analyze demographic characteristics such as age, gender, and region.
- Segment customers by age range and analyze behavioral characteristics.
3. **Exploration and Understanding of Sales:**
- Analyze sales and returns levels.
- Investigate average basket size and top products per product line.
- Analyze the contribution of each region to the company's revenues.
4. **Promotional Activities:**
- Analyze the percentage of products sold with and without promotions.
- Investigate the distribution of sales per day of the week.
5. **Supplier Analysis:**
- Determine the percentage and actual revenues of products sold by each supplier.
6. **Customer Segmentation:**
- Profile customers based on Recency, Frequency, and Monetary parameters.
### C. SAS Visual Data Mining and Machine Learning
7. **Customer Clustering:**
- Analyze RFM data set using SAS Visual Data Mining and Machine Learning.
8. **Association Analysis:**
- Identify associations among product categories in the whole data set and within identified customer clusters.
### D. Instructions
- Address answers to business people in an understandable manner.
- Include charts, tables, and screenshots documenting the results.
- Include SAS code in the appendix.
### E. Datasets Description
- **Customer Table:** Contains customer details such as name, address, gender, and birthdate.
- **Invoice Table:** Contains data about issued invoices including date, customer ID, and payment method.
- **Basket Table:** Contains details about products sold in each invoice.
- **Products Table:** Includes product details such as type, price, and origin.
- **Promotions Table:** Contains information about promotions and discounts.
- **Product Origin Table:** Provides details about the origin country of each product.
- **Suppliers Table:** Includes information about product suppliers.
