a detail-oriented Data Scientist and Analyst with a keen eye for unraveling insights hidden within data's intricate tapestry.
Welcome to my Data Wonderland, where numbers come alive and insights thrive. Whether it's deciphering data's secret language or crafting compelling stories from numbers, I'm here to turn raw data into actionable insights. You can view my RÉSUMÉ, GITHUB, and DASHBOARDS.
Learn more about what I doSome tools I work with:
Excel is a versatile and widely-used spreadsheet software that I leverage for data analysis, manipulation, and visualization. I use it to clean and preprocess data, perform basic statistical analysis, and create informative charts and graphs.
Tableau is my go-to tool for interactive data visualization and reporting. With Tableau, I can transform complex datasets into insightful dashboards and visualizations, making it easier for stakeholders to understand and interpret data.
Power BI is an essential tool in my toolkit for creating dynamic and interactive data reports and dashboards. It allows me to connect to various data sources, transform data, and generate compelling visuals to drive data-driven decision-making.
SQL (Structured Query Language) is my primary tool for database management and querying. I use it to retrieve, manipulate, and analyze data stored in relational databases, ensuring data accuracy and consistency.
Python is my preferred programming language for data analysis and machine learning. I use it to develop data pipelines, perform advanced analytics, and build machine learning models. Its extensive libraries and packages make it a powerful tool for a wide range of tasks.
Machine Learning is at the core of my data science work. I employ various ML algorithms and techniques to uncover patterns, make predictions, and extract valuable insights from data. This enables data-driven decision-making and the development of predictive models for various applications.
Here are some of my projects...
This project is a comprehensive exploration of machine learning techniques to predict the presence of heart disease in individuals. Leveraging a diverse set of machine learning algorithms, this predictive model aims to provide accurate and actionable insights for early detection and intervention in heart disease cases.
In this project, I delved into a comprehensive dataset from a bank containing valuable transaction records and certain information such as transaction type, amounts, customer details, and time stamps. My analysis aimed to uncover patterns and insights within the data using SQL, particularly focusing on distinguishing between legitimate and fraudulent activities.
At Delur Services, a customer-centric company, I focused on optimizing customer satisfaction and return rates. I conducted in-depth data analysis and gave recommendations to help Delur Services achieve a targeted return rate of 5% in the coming year. By leveraging data-driven insights, I contributed to their commitment to enhancing customer experiences and continuous service improvements.
Interactive Dashboard
This analysis utilizes Tableau's powerful visualization capabilities in offering a comprehensive view of KMS superstore's sales performance, providing actionable insights to guide strategic decisions and enhance customer experiences.
Interactive Dashboard
This is an interactive exercise leveraging Structured Query Language (SQL) concepts to solve a murder mystery. In this project, I applied SQL expertise to solve the SQL Murder Mystery. Utilized SQL queries to uncover key insights and solve the case, demonstrating proficiency in database analysis and problem-solving.
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This project involved analyzing Netflix movie data using Python. I investigated whether the average duration of movies on Netflix has been decreasing over the years by creating visualizations, cleaning and subsetting data, and drawing insights from the dataset. By leveraging Python's data analysis and visualization capabilities, I explored trends in movie durations and provided insights into the evolving landscape of movies on the Netflix platform. This project showcased my data analysis skills and proficiency in Python for exploring real-world datasets and drawing meaningful conclusions.
In this project, I analyzed the US Accidents dataset, spanning the years 2020 to 2021, documenting various traffic incidents. This project aimed to understand the patterns, trends, and characteristics of these accidents across different states, counties, and cities. As a Data Scientist, I leveraged Excel's tools to facilitate data organization and analysis, revealing valuable insights for safer roads.
In this project, my role as a Data Analyst was to extract, clean, and analyze Nigeria's economic data spanning two decades (2001-2020) from the World Bank. Using the powerful tools of Excel, I organized this wealth of information into a structured table, and derived a succinct yet insightful overview of Nigeria's economic journey, equipped to inform decisions and policies.
This project was all about data-driven inquiry, including uncovering insights and answering pivotal questions about sales landscape, customer loyalty, outlet type contributions, struggling producers, etc., from the sales data of a bustling store. This project showcased my data analysis skills and proficiency in harnessing the ability of Excel to transform raw data into actionable insights, unlocking the potential for a brighter future for the superstore.
chidimmaidika@gmail.com | +234-806-401-1655