Grant Kemp - Start Making Your Data Actionable: Google Data Studio

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Questions are good. Questions allow us to see the beauty of life. Never stop asking questions.

Peter Cawdron, Hello World (self-published, 2019)

Most people who are seen as data experts or data gurus may seem like they are wizards now, but they were all beginners once. One day, something happened that made them decide that they wanted to start experimenting with a data visualization tool. Maybe one weekend or one evening instead of slumping in front of the TV, they decided to fire up their laptop and start experimenting with a data tool. For them it would have been quite frustrating, as frankly the documentation is usually not great, and examples are often harder to understand. I found on my personal journey that I could sink hours into understanding various concepts and ideas even to do things that I felt were quite basic. I managed to find my way through, but not without a lot of stress and painful learning.

The good news is that we are going to do this journey together. In this chapter, I am going to take you through your first steps with Data Studio and work with you until you are ready to go out and hold your own.

So pull up a chair, make sure you have a nice drink next to you, and we are going to start experimenting with building your very first data report in Data Studio.

I always say you dont find data but rather data finds you. I have worked with countless people across a wide variety of industries, each of whom was at different stages of data understanding and interest. Through my talks at conferences and meetups, I have had the pleasure of encountering people who are at the early stages of their interest in data. What I find most remarkable is just how many different backgrounds people come from. The one common thing they all share is that they found themselves at a challenge or a crossroad where they were stuck. They knew that there was a missing piece in their understanding and were seeking for data to fly in and be the superhero to save them.

I would love for data to be a magic bullet that can simply be switched on to solve problems; however, in reality, finding the data is just the beginning of the journey. For some people, they will get part way down the data road and discover they have enough and veer off to something else they find interesting. For others, they will be thrust forward into the multitude of wonderful new data job specializations that are sprouting weekly.

Data scientist, data engineer, artificial intelligence engineer are all new roles that were quite rare a few years ago but are becoming increasingly commonplace in most organizations. You could argue that to even be a reasonably effective digital marketing manager nowadays takes the level of data literacy that previously would have been required of a data analyst.