About Me
I have a genuine passion for harnessing data to aid clients in making well-informed decisions and advancing strategic planning initiatives. My portfolio comprises a variety of projects that illustrate my expertise in data analysis, visualization, and interpretation, using tools such as Tableau for data visualization, SQL for data querying and manipulation, Python for data analysis and scripting, and machine learning techniques to derive meaningful insights that drive impact. Please explore my projects bellow or for a broader overview, visit my GitHub portfolio.
Summary: Analysis of cafeteria violations in public and private schools across different boroughs in New York City,
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Process:
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Cleaning and wrangling data in Python
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Conducting Exploratory Data Analysis (EDA) with SQL
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Visualizing data in Tableau.
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Goal:
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Identify areas with the highest risk.
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Explore the disparities between public and private school violations.
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Suggest solutions.
Summary: The analysis uses machine learning and Natural Language Processing tools to classify the sentiments of tweets related to airlines.
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Process:
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Data cleaning using the nltk library.
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Vectorization of textual data.
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Tuning of the machine learning model.
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Goal:
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To build a classification model that accurately targets negative sentiments (aiming for a 96% accuracy rate) in order to assist airlines in identifying and addressing customer dissatisfaction issues.
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Summary: This analysis employs a bagging classifier machine learning algorithm to predict the functionality of water pumps in Tanzania.
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Process:
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Data preparation and cleaning with Python
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Application of machine learning for modeling.
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Model tuning for optimal performance.
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Employing cross-validation to test model reliability.
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Goal:
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To develop a practical tool that assists both government and non-governmental organizations in Tanzania with resource allocation for addressing water access issues.
Summary: This analysis employs MySQL queries to examine and comprehend sales trends at three major Walmart branches.
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Process:
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Creation of the database.
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Data wrangling to prepare and clean the data.
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Feature engineering conducted within MySQL.
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Goal:
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To gain insights into sales trends and customer behavior patterns at Walmart branches.
