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Online Retail Analysis

Analysis of sales trends across 38 countries within a year for an online retail store.
Leveraged hypothesis tests to measure the statistical significance of the relationship (correlation) between variables and the difference in means of sales between countries.



 

Python
Hypothesis Test
Correlation
Screenshot (114).png

Work Samples

mPharma Twitter Sentiment Analysis

Sentiment analysis of a healthcare startup, mpharma in Accra, Ghana.

Extracted and transformed about 1300 tweets to uncover public opinions and trends.


 

Python
Power BI
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E-Commerce Retail Analysis

OBJECTIVE:

An e-commerce company needs to enhance customer satisfaction and increase revenue by leveraging targeted marketing and impactful campaigns in its e-commerce operations.

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TASK:

Analysed 541,908 sales records to determine trends, customer segmentation, and customer behaviour across 38 countries a year's transactions.
Measured the significance of correlations between variables and the difference in sales mean between countries using hypothesis tests.
 

Screenshot (114).png
Python
Matplotlib
Data Wrangling
Hypothesis Test
Statsmodels

Restaurant Sales Performance

Analysis of restaurant operation data that seeks to gain insights into sales trends, customer segmentation and menu preferences for tailored approaches in marketing, menu design, customer experience, and ultimately enhancing customer satisfaction and optimising revenue generation.

Tableau
Calculated Fields
Restaurant Sales Performance.png

Telecom Customer Evaluation

Designed and developed a comprehensive dashboard for a leading telecommunications company, providing valuable insights into customer retention, churn rates, demographic trends, and revenue analysis.

 

The project utilised a dataset provided by pwc in partnership with forage, ensuring access to high-quality and reliable data.

 

The dashboard offers a user-friendly interface, empowering decision-makers with actionable information to optimise customer retention strategies, identify potential churn risks, and make data-driven business decisions.

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Power BI
DAX
Image by Kabiur Rahman Riyad

Medical Appointments Analysis

An exploratory analysis of a dataset comprising medical appointments in Brazil, with the objective of gaining insights into the factors influencing patients' attendance or non-attendance at their scheduled appointments.

 

Aimed to identify patterns, correlations, and potential predictors that contribute to appointment attendance rates. The objective-driven approach provided valuable insights into the dynamics of patient behaviour. 

Python
Pandas
Matplotlib
Seaborn
Doctor Examining Patient

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  • novypro
  • Tableau
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