Maven Space Challenge

Intro

In 1977, we already launched 110 rockets successfully. However, we have exceeded this number after 40 years, and reached our highest peak in 2021. Why didn't we increase the number of successful launches continuously? Are there any factors that lead us to a halt?

Therefore, I'm going to compare 1977 and 2021.

Analysis

1. In 1977, Russia launched the highest number of successful rockets; however, in 2021, China had the highest number of successful launches.

China has gradually increased its successful launches past 40 years. Although Russia has the greatest number of successful launches, its successfully launched rockets have decreased every year. However, the rocket launch success rate can be more important than the amount of successfully launched rockets, which is something I can dig into in the future.

2. Successfully launched rockets in 1977 were all retired before Aug 2022, and the new rockets are on their way.

Technology can be played as an important role in the rocket market. The new rockets might have higher chances to reach space. In 2011, there was a tie between the number of active and retired rockets. Ever since then, successful launches are increasing.

3. More and more companies have joined the rocket experiment.

Back in 1977, there were only 7 companies that joined the space experiment. In 2021, the number had been expanded to around 20 companies. More and more companies are putting money and effort into space experiment, and we could expect companies like CASC or SpaceX becomes the leader in rocket technologies.

Reflection

This is my first Tableau Challenge. I spent about 8 hours finishing this post, and I definitely learned a lot from it. Below are my takeaways:

1. I should plan first. Set a goal, and I will know what I should dig into and what I should give up.

As an example, if I could first decide on my topic as comparing the launching success between 1977 and 2011, I won't spend lots of time on the line charts. (I originally split the timeline into three parts, and I realized it's unnecessary.)

2. I should use the treemap wisely. On the other hand, maybe a treemap is not the best way of presenting the information.

Inspired by Eva Murray, I should limit the variables inside a treemap, so every number can be shown up in detail. OR, because my goal is to compare the number of companies in 1977 and 2021, I can use a line chart, make every company gray lines, highlight the top 5 companies with the most successful launches, and possibly draw a line on both 1977 and 2021.

3. Learn to discard the information.

I'll say it is the hardest condition of all. I should be wise in selecting useful data, since not every piece of information or findings is suitable to be shown on a dashboard. Take this dashboard as an example, besides putting Kazakhstan under the spotlight, researching Russia is wiser.

Conclusion

The challenge has so much fun, and it also makes me understand what I'm lacking. I will make sure to learn from this experience, and reflect on what I've learned in the next dashboard. The next project will be a machine learning project I have done back in school! I hope I can publish it ASAP lol. See you soon!

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