Project 1 – PS4 Games Global sales

I’m going to show you how I created my first Power BI project using PS4 games global sales data from the Kaggle database. Power BI is a great tool that allows you to create interactive dashboards and reports with ease. I was curious to see what insights I could get from the PS4 games data, such as which genres are the most popular, which regions have the highest sales, and which games have the best ratings. Here’s what I did and what I learned from it.

The first step I did was to import the data from Kaggle into Power BI. Kaggle is a platform that hosts datasets from various domains and challenges. The PS4 games data was uploaded by a user named Rush Kirubi and it contains information about 1034 games released for the PS4 console from 2013 to 2019. The data includes the name, genre, rating, publisher, developer, release date, and sales figures for each game in different regions. To import the data, I downloaded the CSV file from Kaggle and then used the Get Data option in Power BI to load it into the query editor.

You can find the dataset here: https://www.kaggle.com/rush4ratio/video-game-sales-with-ratings. To import the data, I downloaded the CSV file from Kaggle and then used the Get Data option in Power BI to load it into the query editor. I did some basic transformations and cleaning on the data, such as removing null values, changing data types, and renaming columns. After that, I loaded the data into the Power BI model and started creating my project.

Here are the questions that I wanted answered:

  • Who most bought games per region?
  • Which game sold the most?
  • In America, which game sold most?
  • Which was the publisher that most sold globally?

I wanted to take it a step further and experiment with filters and other types of data. As such, I decided to obtain results for the most popular games in Europe, categorized by genre. To answer this question, I filtered the dataset by Europe region and grouped it by genre. Then I calculated the total sales for each genre and plotted them in a pie chart. Here’s what I got:

Working on this project one of the things that I learned was how powerful power PI can be. It has so many features and functions that can help you create stunning and interactive visuals. You can also connect it to various sources of data, such as Excel, SQL, web pages, and more. You can even use it to create custom visuals using R or Python. I am excited to try other data. The possibilities are endless!

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