Ramon's Data Analytics Portfolio
About Me
Hey there! My name is Ramón Paynter Portuese. I like a multitude of things. I am a Colorado Native and I am passionate about my friends and family and enjoys getting outdoors. I'm a curious problem solver with a desire to overcome real world challenges.
I have spent the last eight years working in healthcare and have grown a lot. What got me into data analytics was wanting to continue my education and having a passion for technology. I enjoy data analytics because it allows me to utilize my technical mindset working with data and various tools while also having me collaborate with people.
I have lots of professional goals, ultimately I want to become the best data analyst that I can be and help serve whatever team and mission that I am blessed to be a part of.
There are many opportunities that I am open to but in particular I am looking at working for a company that is based in healthcare, or data privacy because those are the things that I have the most experience. I’d also like to mention that I have natural inclinations toward marketing, E-commerce, and data privacy/security. Ultimately the opportunity that I want the most is one where I can put my employer and myself in a win-win situation where we can both grow.
I am interested in data analytics for many reasons. Like I stated before, I like the opportunity to utilize both my technical mindset as well as my more creative mindset with data analytics. I derive lots of meaning by creating data analysis that solve real world problems.
Portfolio Projects Section:
This section below has three Data Analysis Projects
1. Flavors of Cacao Analysis
•What this visualization to the left is doing is letting the viewer know that the companies represented show their average rating per bar. Based off of the data one can see Chile is the country that has the companies that produce the highest rated chocolate bars on average. However there are other countries throughout the world which have high rated chocolate bars on average such as Guatemala 3.350, Norway 3.333, Poland 3.375, Vietnam 3.264, and many others. For the complete data analysis please click on the blue box below!
2. Instacart Customer Analysis
•This visualization to the left are the spending flags that go over the young adults, middle age adults, and senior adults. This is done by Region and frequency. The three are split up between low income, middle income, and high income. For the complete data analysis please click on the blue box below!
The Instacart Analysis involved many things and was a great integration of Excel and Python. In this analysis I overcame key customer issues by analyzing customer data using Excel, Python, Pandas, and Matplotlib. The analysis helps one understand trends among different groups. The analysis also provided insights into customer behavior based on the demographics.
3. Retail Inventory Analysis
The Retail Inventory analysis provided a great opportunity to find out which video games are popular and how to integrate a brick and mortar business with online streaming. With this analysis, I faced inventory challenges, but eventually overcame them and generated recommendations to improve company strategy by evaluating and providing guidance on pricing, marketing strategy that was based on location, and staff recommendations, refined the strategies and had inventory success.
This particular visualization to the bottom left has the sum of the sales by year for Three Separate Regions: North America(Light Green), Japan(Dark Green), and Europe(Gold). North American has historically performed the best and peaked in 2009. Marketing Efforts therefore need to be focused on North America. For the complete data analysis please click on the blue box below!
This Flavors of Cacao Analysis went over many different things. In the analysis, I had to solve product problems by studying product data using Python, Excel, Tableau, and Pandas to find ways to make it better, thus resulting in improved product quality and valuable insights for enhancement.