SQL and Tableau Project Portfolio
Utilizing a dataset unique to my interests
This past year has been a wild ride in the world of data. I was not fully aware of the tools, education, and resources fully available.
I dived in and obtained my Google Data Analytics Certificate. This provided deeper knowledge of spreadsheet formulas, SQL, data visualization using Tableau, and many other useful skills.
What I’d like to mostly focus on is a data project that I recently worked on using ChatGPT, SQL, and Tableau Public.
In my studies, I have found that it is important to build and maintain a strong portfolio to demonstrate my knowledge and skills around data.
I also found that whatever project you are working on, if the data is around something you are interested in, it is much easier and makes for a smoother process.
I present to you my data project.
Top 10 board games from 1989–2021
The first thing I did was I went to Kaggle and downloaded a board game dataset that someone already spent the work on to scrape data from the Board Game Geek website.
In the future, I plan to do the same thing to not only demonstrate my skills and abilities around Python but to also get a more recent pull of the dataset.
This dataset, though, was sufficient as it had 20,000+ rows of board game data with names, rankings and the year the board game came out, etc.
Upload the board game CSV files to Google Cloud Big Query
The CSV file was then uploaded to Google Cloud Big Query, where I could then start writing my SQL query.
I had a vision of what I needed the data to look like when queried so I pulled up chatGPT and asked:
“If I have a list of board games with the year it came out and top rankings, write a SQL query that pulls all the top 10 board games for each year by 10 rankings for each year.”
I plugged in the first snippet of the SQL query to the correct names but had to do some modifications to the query so I told chatGPT the following:
“Table name is allboardgames, the row of header data is — ID Name Year Published Min Players Max Players Play Time Min Age Users Rated Rating Average BGG Rank Complexity Average Owned Users Mechanics Domains. Write the SQL query again to pull the top board games by “Year Published” each year and show the top 10 board games using “BGG Rank”
Here is what ChatGPT modified and this time worked great. Here’s the SQL query:
This allowed me to have a list of top-ranked board games by year. I downloaded a CSV file in this format and connected it to Tableau Public.
Visualized Top 10 Board Games by Year Using Tableau Public
I was able to display all the top 10 board games by year to allow me to see a snapshot over 20+ years. You can view the link or explore the image below:
My Findings
The top board games matched up with the feedback I was gathering from other sources. I did a lot of research on YouTube to research what others were saying and recommending as being the best board game.
Here are a few games that are now in my possession based on this research:
- Wingspan
- Everdell
- Lost Ruins of Arnak
- HeroQuest
Here are games on my bucket list that I plan to get based on this research:
- Sleeping Gods
- Brass
- Scythe
- Great Western Trail
Here are other games not in the top 10, but additional research convinced me to also have in my board game repertoire:
- Above and Below
- Ark Nova
Further Analysis
Once again, to get a complete analysis in the future, I would utilize Python to scrape Board Game Geek website and also YouTube and compile a further analysis of top board games that have been highly rated and recommended. For now, I am satisfied with my findings.
I am looking forward to becoming more fluent in SQL and Python. ChatGPT is a great way to reverse engineer the process because now I can go back and study the query and have a better understanding of how to pull specific data sets.
