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Tools for data analysis

I often get questions about tools for data analysis. Great topic for a blog post, I thought. But, when I started to write it became so massive that I realised I need to make a whole series out of this topic.

Here are all the different takes I have on tools for data analysis. Big and small.

Finding the best tools for data analysis

With a background as a tech journalist (– a long time ago), I have this weird interest in new technology. Whenever I find something new I can try, I get excited. I love spending time on ProductHunt to see what new products that might help me do my job better. Maybe not the most normal thing to do on a Sunday night, but I love it.

I’m always looking for two types of tools:

  1. technology that can simplify or even automate part of my current job, or
  2. technology that can give me possibilities that I don’t have today.

However, I started like most people: writing reports, making presentations and sometimes using spreadsheets to do calculations. Most of my time is still spent putting thoughts on paper. My every day “tech stack” is still pretty basic.

Everyone can learn data analysis

Since I’m going to talk about tools for data, I want to say that my background is not in statistics or engineering. I’ve learned most of my data skills by doing it by myself. I started testing with small side projects. And for me, taking MOOCs and watching tutorials online has been a pretty good way for me to learn.

But most importantly, I learned it all was that no one else around me knew how to do data analysis. I quickly realised that if I didn’t try to figure out how to do it on my own, I wouldn’t have any quantitative insight at all.

Not using the data I had access to in some way felt more stupid than to try to do some data analysis on my own.

Articles about Tools for Data Analysis

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