B I O

I am an aspiring data professional coming out of IT with a passion for data-driven storytelling and problem solving I am a critical thinker with a strong agenda.

I will provide data solutions and valuable insights. I recently completed an extensive training to enhance my data analytics skills. I am a Power BI specialist, creating reports and dashboards and models to identify key insights. I also have strong Python skills for data engineering & analytics projects.

With years of SQL experience, I can write complex queries to extract and transform relational data. With my skills in Apache Airflow, I can create and maintain scalable ETL / ELT pipelines in Python. With my hands on Airflow experience, I can develop, operate and manage complex data operations.

Airflow Pipeline

Google Play Store Dataset

project description

The research uses data analysis tools to look for trends and discover patterns. I tasked myself to use Google Play Store dataset to uncover some applications on the Google Play Store that do better than others, receiving good reviews and thousands of downloads. The project will outline certain trends that will offer suggestions for improving app performance on Google Play Store.

The business problem

Using data chosen from the Google Play Store that contains 10,000 apps to analyse key metrics such as number of installations, ratings and categories so we can learn more about how to better understand what makes an app highly successful so we can improve the number of installations and user engagement.

Task

Data import and cleaning:

• Importing the data set into Excel
  
• Identifying and correcting data errors, discrepancies and inconsistencies
  
• Removing duplicate or irrelevant data
  
• Restructuring and organizing the data for analysis
  

Data exploration:

• Examining the data across to identify trends, correlations and outliers
• Using filters, formulas and pivot tables to extract relevant information from the data
• Calculating key metrics and performing comparisons across different groups

Data visualization:

• Using Tableau to transform the raw data into insightful dashboards and interactive visualizations
• Creating charts and graphs to illustrate patterns and relationships within the data in an intuitive, easy-to-interpret format

Reporting and analysis:

• Preparing a comprehensive report summarizing my analysis process, key findings and business implications
• Identifying areas of opportunity or underperformance based on the data
• Recommending strategic, data-driven solutions to improve processes, performance and outcomes
  

Actions

Data cleaning:

• Removed 483 duplicate rows
  
• Using the filer tool removed the empty rows
• Changed the price column since it's showing as a string column
• Changed the size from M to MB and K to KB

Data exploration:

• Using pivot tables found a lot of nan values in the ratings column, various with device in the size column and null values in the size column
  
• Grouped the ratings for ease of use as the data would be inaccurate
• Analyzed the data by calculating metrics like averages, percentages

Data visualization:

• In Tableau, I created charts and graphs to visualize the data, spot trends and identify patterns.
  

Results

1. Based on the analysis we have discovered that the most popular category is the Family category with 1826 apps, accounting for 19% of all apps and the average rating is 4.2 out of 5 indicating that it's a successful category.
2. With over 5000 apps receiving above 4-5 rating, it shows that the everyone content rating is the most favourable rating. It shows that a large number of apps cater to all ages.
   
3. The massive gap in download rates, with free applications getting 92.2% of downloads compared to paid apps getting 7.8%. This might suggest that users are likely to try free apps more which may or not eventually lead them to decide whether they want to get a premium version or ad-free version of the app.
   

dataset

https://www.kaggle.com/datasets/lava18/google-play-store-apps

portfolio

https://docs.google.com/document/d/1IuISY_ln6ObUZwb32IEBY6ubZ83IHf37THSl0JhSsq4/edit?usp=sharing

Tableau

https://public.tableau.com/views/Google_16898027146250/Sheet6?:language=en-US&:display_count=n&:origin=viz_share_link