A prospective and detail-oriented data analyst with experience collecting, transforming, organizing and visualizing data for analysis
in the field of marketing. Eager to contribute to team success through hard work, effective communication, and excellent
organizational skills. Performed and cleaned a retail dataset up to 500,000 rows using RFM analysis in Python to find 10 types of
customer within 1 week.
Feel free to contact me
Microsoft PowerPoint Python PostgreSQL Microsoft Excel Data Analysis Microsoft Power BI
| User Name: | eddyflorentus |
| Account Type: | Personal Account |
| Date Registered: | 27/02/2023 10:24:24 WIB |
| Last Seen: | 27/02/2023 10:54:25 WIB |
| Provinsi: | Jawa Timur |
| Kabupaten: | Kab. Kediri |
| Website: | https://eddyjagodata.com/ |
| Online Hours: | 0.49 |
| Projects Won: | 0 |
| Projects Completed: | 0 |
| Completion Rate | - |
| Projects Arbitrated: | 0 |
| Arbitration Rate | - |
| Current Projects: | 0 |
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2022: This is a group project assignment to analyze Yellevate�s client disputes. Yellevate defines disputes as clients expressing dissatisfaction with the company�s services and refusing to pay for them.
2022: This is a group project assignment to find which conditions increase many traffic accidents. In fact, the number of accidents happened to non-drunk driver. The goals of the analysis is to find the solution to reduce the number of traffic accidents.
2023: This is a individual project assignment to Identify the most disciplined and undisciplined employees and divisions. I cleaned 6 datasets in using ETL processing and performed Data Modeling to connect the datasets by using star schema and snowflake schema.
2023: This is a individual project assignment to to identify opportunities for best-selling
products. I cleaned 7 datasets using python to find 7800 outliers and to help analyzing accurate data. I Performed over 20 DAX in power BI to get KPI metrics such as GMV, AOV, APF, Monthly Sales, and Weekly Sales.
2023: This is a individual project assignment to to identify all customers such as loyal customers and lost customers to help decision making. Cleaned and Analyzed dataset up to 500,000 rows using Python to find trends and customer segmentation. I executed over 20 DAX in power BI to get KPI metrics such as GMV, AOV, ARPU, Monthly Sales, and Weekly Sales
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