This repository sample projects that I undertook during my spare and practice times. In this Project Session, I work on projects in Excel, Power BI, SQL and Python.
I categorise projects into Data Cleaning, Analytics, Data Visualizations and Full Cycle projects.
In these projects, I use a step by step approach to clean and prepare clumsy datasets.
I document each of the steps taken and try to explain the reason for that step.
In these projects, I ask questions from given datasets. These datasets will be usually cleaned. In the event where the data is not cleaned, I clean and preapre it.
I analyze these datasets and answer the questions to gain valuable insights that can be used for strategic decision making.
In these projects, I tell stories from the given datasets using visualizations. Particularly, I adopt Microsoft Power BI, Matplotlib and Seaborn for these visualizations.
In the near future, I will be using Tableau for other visualizations.
Then, I provide summary notes with insights using markdown cells or readme files.
In this section, I use the Data Science full cycle to undertake the projects. Particularly, I employ the CRISPM-DM framework as a guide.
I sub-categorize these projects into Data Analysis and Machine Learning projects.
The Table showcases summary details of projects.
S/N | PROJECT CATEGORY | PROJECT NAME | PROJECT DESCRIPTION | STATUS | TOOLS |
---|---|---|---|---|---|
PP1 | Full Cycle Project (Data Analysis) |
Product Sales Analysis | Started | Python | |
PP2 | Full Cycle Project (Machine Learning) |
Employee Churn | Yet-To-Start | Python Power BI |
|
PP3 | Data Visualization | Human Resource Analysis | Yet-To-Start | Power BI | |
PP4 | Data Visualization | Retail Sales Data Analysis | In this project, I analyze sales records of data from a retail chain stores, Groupe Darko Retails. | completed | Power BI |
PP5 | Data Visualization | Fiancial Budget Analysis | Yet-To-Start | Python Power BI |
|
PP6 | Analytics | Store Retail Analysis | Yet-To-Start | Excel | |
PP7 | ML Deployment | Auto ML App | In this project, I develop a streamlit app that automates exploratory data analysis, trains machine learning models with a user's dataset and downloads the best performing machine learning model | Completed | Python Streamlit Pycaret |