프로젝트 (1)

[Summary]
Introduction:
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This case study is done upon the customer data of Databel, a telecom company in US.
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The objective is to analyze the churn rate of Databel's customers, deliver extracted insights, and propose following solutions to the managers.
Context:
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Databel that has been the market leader of the industry for years has a concern over its churn rate of the customers since the competition is more fierce than ever. On top of this, Databel wants to know the preferences of the customers deliver better service.
Exploratory Data Analysis
Data Cleaning:
Data Cleaning Checklist
1. Are the data's width and row allocated perfectly? 2. Are there any unnecessary names and words that need to be replaced? 3. Are there any disturbing capitalized data that needs to be in lower-case? 4. Is all the data organized being easy to read and analyze? (e.g. unnecessary spaces) 5. Is there any data that needs to be split? 6. Are there any duplicates? 7. Are there any blank cells? 8. Are there any error cell? 9. Is the header formatted well? 10. Turn and turn-off gridlines to see the data more clearly.
Customer Churn Rate Analysis
Excel
Churn Rate
Data Analysis
[Summary]
Introduction:
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Identifying distinct customer segments within a heterogeneous customer base was the primary challenge, which would enable the implementation of more targeted and effective marketing strategies.
Context:
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A company requested a robust model to segment customers based on their behavioral and demographic characteristics, ensuring that marketing efforts could be precisely aligned with customer needs and preferences.
Exploratory Data Analysis
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The established graphs and maps based on the current dataset did not provide the most meaningful insights as there were lots of overlaps
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Therefore, feature engineering needed to be deployed
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Also, the dataset underwent any possible outliers in age; then grouped the ages data into young, middle, and old groups.
Marketing Campaign Customer Segmentation
Data Analysis
Python
Statistics
Summary:
Overall, the advanced excel visualization tools are touched in this project and used accordingly.
Introduction:
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This project was initiated in an attempt to upscale the level of data visualization skills in Excel
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The objective is to provide advanced data visualization dashboard of customer data from a company operating in US using Pivot Table, Pivot Chart, and VBA.
Dataset:
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The dataset had 5782 features with 10 different categories
Exploratory Data Analysis
Data Cleaning:
Data Cleaning Checklist
1. Are the data's width and row allocated perfectly? 2. Are there any unnecessary names and words that need to be replaced? 3. Are there any disturbing capitalized data that needs to be in lower-case? 4. Is all the data organized being easy to read and analyze? (e.g. unnecessary spaces) 5. Is there any data that needs to be split? 6. Are there any duplicates? 7. Are there any blank cells? 8. Are there any error cell? 9. Is the header formatted well? 10. Turn and turn-off gridlines to see the data more clearly.
Sales by scale of revenue and number of sold
Delivery App Customer Segmentation
Excel
Visualization
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I collected and analyzed 39 current Data & Business Analyst job recruitment posts for personal excel data analysis project. I especially collected the data from international companies rather than completely local ones.
Top 10 Skills required to work in international companies as data analyst:
Learning programming languages like SQL, Python, and R is super important
SQL is required more often than Python or R; therefore, it will be important for me to prioritize mastering SQL first.
Data Visualization skill discovered to be required second most.
While the companies demanded different visualization skills, Tableau was required the most and followed by Power BI, Excel, Qlik, and Looker Studio.
And of course, being bilingual and holding bachelors degree were basic requirement to go through the interview process in international companies in Tokyo.
Having domain knowledge, communications skills, and problem solving skills were also required as the works require delicate synergy among lots of stakeholders to actually bring the nutritious results.
Top Skills required for Data & Business Analyst in Tokyo
Excel
Data Analysis
Visualization
Summary:
Objectives:
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This case study is done upon analyzing dataset of VanArsdel and its competitors.
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The datasets include:
1. Sales-dataset
>Revenue
>Units
2. Products-dataset
>Category
>Currency
>Manufacturer ID
>Product Name
Analyzing a company’s market competitiveness
Power BI
Data Analysis
Visualization