Google Data Studio most common questions

This article is a transcription of our Youtube tutorial. 

If you want to learn Google Data Studio from scratch; if you want a better way to tell stories and present your data; if you want to learn data visualization—a must-have skill in your company, career, agency, startup or whatever you do—these videos are for you. 


Hello, I’m Juan, and I will be your Google Data Studio instructor.


In this introductory class, I will address some of the common questions (and misconceptions) people have about Google Data Studio.

What is Google Data Studio?

Google Data Studio is a free Business Intelligence software—which is different from just a data visualization and reporting tool. 


It is more similar to solutions like Tableau, Looker, Power BI, than it is to visualization-only tools like Klipfolio, Databox, and DashThis (which are mainly used for client marketing reporting).

What is the difference between Data Visualization and Business Intelligence software?

With both, you can create dashboards and reports. Business Intelligence tools, though, let you transform your data. 


As Klipfolio correctly says on their site, they’re a great alternative if you want to visualize the data as it comes from your data sources.


Business Intelligence tools, On the other hand, let you create metrics and dimensions, they let you run functions and formulas,  they let you blend your data sources so you can combine your CRM and marketing data in one report, for instance. 


In general, Business Intelligence tools are much more flexible, so you can make more specific questions to your data.

How hard is it to learn Data Studio?

Honestly, the learning curve to cover the basics may take a few hours


Google Data Studio is meant to help non-technical users, or people without SQL knowledge, build their reports. 


So, for basic reports, you don’t need to be a programming or statistics expert.


Also, its layout is friendly; it’s a drag-and-drop, Google-like interface.


Eventually, when you become better at reporting, you will have more specific queries and questions you want to answer with your data, where you may need to understand the basics of SQL and regular expressions. 


However, if you’re an intermediate Sheets or Excel user, you will be comfortable with Data Studio — functions and formulas work pretty much the same.

Google Data Studio vs. Power BI and Tableau

Fast answer: Tableau and Power BI are more complete solutions than Google Data Studio. 


But, perhaps, they’re not the best for your needs. 


What do I mean?


They have better ways to join your data sources, visualizations are more detailed, and offer better statistical analysis. 


A quick example is, with Tableau, you can instantly visualize Standard Deviation; with Data Studio, you will need a manual setup. 


However, unless you’re an experienced data analyst, I’d say Google Data Studio will be good enough 90 % of the time. 

An outstanding difference is that Data Studio is free, being quite powerful.


 I’m not talking about a freemium solution or a free trial. It’s free. 


And Power BI and Tableau are paid solutions that may end up being expensive for most small businesses. 


Why not using Sheets or Slides to present data?

Don’t do that. 


Slides are for doing keynotes, but not to present data with a context in a dynamic way. You want users to play and filter data to know the full picture. 

Yet, I acknowledge many businesses take screenshots from different apps and paste them on slides. That’s…weird?


Google Sheets, on the other hand, is a great spreadsheet tool, but it falls short when it comes to data visualization. It’s not friendly as a dashboarding tool—, especially for non-technical users. 


Just for the record, you can connect Google Sheets to Google Data Studio, so you don’t need to re-prepare your data!

What are some Google Data Studio use cases and examples?

It’s great you made it to the end of the video. 


While it’s a popular tool within the digital marketing community, you can connect and visualize virtually any data source.


But, we will cover common use cases and examples in the next video.


So thanks for watching and keep reporting!


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