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Frenquently asked questions

Si has visitado mi sección de contact ya habrás visto que te animo a preguntarme lo que quieras e intentaré ayudar en la medida de lo posible. No obstante, hay preguntas que en los últimos años me han hecho con cierta frecuencia, así que paso a responder algunas de ellas a continuación por si te ayudan a ti también.

What books do you recommend to learn about data visualization?

Nowadays we can learn a lot with digital media: videos, tutorials, blogs, and so on. But personally, I always like to have some books for reference for the topics I’m more interested in. If you’re like me and enjoy having physical books, here’s a short list that for me was is very useful no matter if you want to start learning about data visualization or if you already have experience but want to dig deeper in the topic and learn more.

What skills you consider more important to become an analyst, data visualization expert?

When we talk about data analysis, data visualization, data preparation, or any other skill data related, what we expect is that the fundamental knowledge is very technical: programming in Python, mathematics, statistics, statistical packages such as R, data visualization libraries that require programming knowledge such as D3.js, etc. Those technical skills are always great to have, and I always try to find time to learn them. But I think one big mistake we normally do is focusing too much on technical skills and forget about others that are as important as those ones. Unless you really want to become a pure data scientist, dedicated entirely to programming and statistical modeling, algorithms and predictions, anyone who is dedicated to analysis and data (and even those data scientists) is faced with the following tasks every day:

1. Understand causes and consequences of your findings and analyses.
2. Share those findings with others.
3. Ensure other people easily understands those findings.

Based on my experience, those needs means you need also three very specific skills if you want to become a good professional in the data world inside any company:

1. Curiosity.
2. Communication skills.
3. Ability to synthesize.