It’s no secret, I guess, that the past year 2022 was probably the craziest and most exciting year I’ve ever had so far: Together with my partner, we bought an old sailboat and decided to live on it and travel the world together ⛵. So it was obvious to me, that the topic of my first private data analysis project has to deal with my new passion - sailing! #sailingnerd🤓

This data analysis aimed to go through the general data analysis phases using our sailing records, apply statistical methodologies, and share the results.

Phases of Data Analysis

Whether evaluating business-related data, industry-specific data, or maritime data, every data analysis goes through the same six phases:

❓ Ask

The first step is to define what potential problem has to be solved and what the expectations are. This project aimed to collect all the data from our sailing trip and discuss statistical aspects, such as the absolute distance, average speed, etc. A regular ‘problem’ will not be solved.

📂 Prepare

The next step is to collect and provide the available data. In this case, we downloaded our saved sailing routes from our maritime navigation chart provider and stored them locally on hard disk. We also enriched the data with additional information on the current speed at the recording time and the distance traveled.

⚙️ Process

The data set is then examined for errors such as missing data, incorrect data format, redundancy, or outliers in measurement points. This step is also called ’the cleaning’ of the data and needs to be done before the actual analysis begins.

🔎 Analyse

During the analysis, the data is now transformed, and scores are provided. In addition to the overall consideration of the records, it was also worked out which routes among themselves were the fastest or the longest sailing trips.

📈 Share

After the analysis, it is a matter of presenting your results to the relevant stakeholders. Visualization is very crucial here. With the help of diagrams and images, complex relationships are presented so that they become easier to understand. Instead of a table of countless position data, these are shown as a route on a map, for example. In addition, the route is colored to show how fast and where we sailed on our route.

🎯 Act

In the final phase, actions should be derived based on the findings that could previously be obtained from the data to achieve our business goals. In my case, however, no problem was defined at the beginning, which also means that no actions are the consequences… Except perhaps in the next year trying to achieve a better average speed 😉

Check out our Sailing Track Analysis!

Are you interested in looking at my Jupyter notebook for data analysis of our sailing route? Then you can have a closer look at my results at our GitHub repo.

Or take a look at the interactive map of our 2022 sailing route here 🗺️.

GPX Tracking Sail Analysis notebook repository

Also if you need help with analyzing your data, just contact us at info@nola-ventures.com.