Viktorija's Portfolio Project

Viktorija's Portfolio Project

Viktorija Juskevica


vik ida tg

In the final project brief for the Intro to Data Analytics Course, students are asked to imagine themselves as analysts for a new video game company, GameCo, which wants to use data to inform the development of new games.

Below is Vik’s descriptive analysis of a video game data set to foster a better understanding of how GameCo’s new games might fare in the market.

Hi Vik! Talk us through your educational and professional background. 

I did a Bachelor’s degree in Economics and Business Management, and I’m now the CRM manager on the marketing team here at CareerFoundry!

What did you enjoy most about the course?

I really enjoyed the ongoing communication with my mentor and tutor. Together, they kept me super motivated—and I felt like all my questions were answered. 

Tell us about this portfolio project. 

This project allowed me to look at data from various viewpoints, and I really feel like I’ve developed a  structured approach to gaining insights from data. Going forward, my hopes are to continue improving my data analytics skills, and start using them at my job as a CRM manager.

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Project reflections

In my opinion, the most interesting point that GAMECO’s executives can take out from the data analysis is that the proportion of sales among different geographic regions have changed in the last 5-7 years. This insight is of significant importance because it will (1) allow the executives to change the resource distribution in the geographic regions in the upcoming years and (2) promote further research into customer markets and their behavior patterns in each geographic region. All of this will allow GAMECO get a better understanding of its various customer segments and their needs, which will result in a higher return on investment for the company.

To gather the insights from the data given to me I followed the following steps:

1. Data was cleaned

This has been done in order to perform an accurate analysis of the data. Working with “dirty” data can lead to wrong conclusions and, hence, hurt the business.

2. Data was narrowed down to the time frame from 2005 to 2016This has been done in order to focus on the last decade of the company’s operations and spot patterns that happened in the recent years, when the global sales of GAMECO started to decline. The data before 2005 was disregarded for this analysis, as it is “outdated” and doesn’t bring value to the current situation in the company.

3. Necessary variables were created to showcase the required information

In order to look into how the proportion of global sales has been distributed among different geographic regions over time, I’ve created a variable called % of sales (see below).4. Several charts were created to demonstrate the insights in an visual wayAs a way of presenting the insights, I’ve decided to go with line charts and labeled all the necessary parts of the graphs.

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Below are the charts that were included in my final presentation.

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(1) GAMECO’s global sales from 2005 to 2016.

This chart shows us that total GAMECO sales began a sharp decline starting from 2008 that continues up to this date. This insight allows us to highlight the main problem the company is facing. As the next step, we can look further into this issue.

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(2) Proportion of GAMECO’s regional sales from 2005 to 2016.

This chart demonstrates us the second insight – proportion of regional sales did not stay constant, but rather changed over time (ex. proportion of EU sales surpassed the proportion of NA sales in 2016). This insight encourages executives to further investigate the situation in each geographic region and better understand the behavioral patterns of the consumers.


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