Learning how to handle data

Apart from some Mathematics in secondary school (a time that is now far behind me) I have not gained any further knowledge of statistics. I also have no scientific background and my knowledge of Microsoft Excel is not much greater than that of the average person.

Learning on the go

Be part of my learning curve

You may wonder why I mention it so specifically that I am at the beginning of a learning dive into data. Now, that is, to manage expectations here on this blog. Do not expect expertise or new insights if you have landed here as a data scientist. (In fact, I can probably learn a lot from you then.)

I share my learning path so that everyone else can also learn from it. In my opinion, dealing with data and better yet, making soup out of it are essential skills that every professional should have. The world around us is increasingly overgrown by data, machine learning, and algorithms. Whether it’s a recommendation on Netflix, the messages you see on social media or the amount of your insurance premium. Data is what drives our world.

Follow me on my path

Enjoy my knowledge

So there is a good chance that it will be a mix here since I don’t have a well-thought-out plan. In addition to sharing knowledge and information that I have gained myself, I will also distribute the books, articles, and podcasts that I think are worthwhile. Be sure to also subscribe to the newsletter, because then you can be sure that you won’t miss anything.

In addition to data and data processing, I will also delve more into analysis and what makes a good analysis. Because an analysis starts with making choices and drawing up an intended goal. In addition to choosing a clear approach, there is also a good chance that your research will be biased. Retrospection and helicopter vision are therefore necessary.

An attempt at prediction

I think…

With the right data and the right approach, you can do two things:

1. Analyzing
2. Predicting/Forecasting

The first, analyzing, is often used to see why something went the way it did and with that knowledge, you can then make adjustments. For example, you find out why visitors stay on a certain page on your website for such a short time.

The second aspect, forecasting, is a whole different game. You then use all the data to think about what it might be like in the future. Prediction is kind of the holy grail right now.

• Know how a stock price is going to move
• Know what the weather will do
• Know how a virus spreads
• Know how a presidential election ends

Initially, I will only indulge in analytics, but who knows, maybe one day I will also focus on forecasting. Before I do that, I will first read the books Superforecasting by Philip Tetlock and The Signal and the Noise.