Video Game Data Analysis

Emma Ojukwu

Marketing Analytics Specialist
Market Researcher
Data Analyst
Microsoft Excel
Microsoft Power BI
SQL

The Process 🔎

I began by downloading this dataset https://www.kaggle.com/datasets/gregorut/videogamesales from Kaggle.com
The data was stored on EXCEL. Here I sorted, filtered and formatted the data.
I then used SQL for data manipulation. I was able to remove nulls and model the data by creating and managing tables. I grouped and joined tables I thought would help me analyse the data in greater detail. For example I created a Genre, Publisher and Platform Table.
I uploaded the data onto Power Query where I performed data cleansing to transform the data. i was able to aggregate the data by summing up totals for easier analysis, creating new columns and adding measures.
I loaded the data onto PowerBi Desktop where the model view helped me connect tables and create relationships. This made it easier for me to visualise data. After visualising all the data I created drill through sections that will assist anyone who is trying to weave through the dataset.
North America Drill Through Section
North America Drill Through Section
I put my analysis into words and suggested ways in which certain regions could increase their sales or maximse their sales. Here is an excerpt:
How could Japan increase console sales?
The clustered line chart displays which regions reached the target profit margin which is $63.55 approx. considering the average selling point for a console today is $45.39. Japanese sales are considerably low here to North American sales, none have met the target. The reasoning here could be that other console that have not been considered in the data are more popular in Japan. To increase sales, publishers could release demos to create hype around a potential new release. Partnering with Twitch streamers is a fresh and exciting way to market your console. xQcOW the most popular streamer on Twitch averages around 73,000 viewers every time he goes live. Partnering with him means plenty more eyes on your console.
I used Powerpoint to present my data.
Goals
• Use SQL to manipulate the dataset • Use Power Query to perform ETL • Use Power Bi to analyse and visualise the data
Suggest data driven marketing decisions.

Takeaways 📣

Things I would change:
Platform and Console are used interchangeably throughout the data analysis. I should have stayed consistant with 1 label as it could cause confusion to those who read the data.
I was not able to share my Power Bi project since I do not have a company account. This inhibits viewers from interacting with my data analysis. Therefore, the immersive quality is eliminated.

2023

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