How to Leverage Google Data Studio

Alejandra Budar
Fields Data
Published in
3 min readJun 23, 2021


In previous posts, I introduced you to Google Colaboratory, as well as Python libraries that can be used for data analysis and data visualization. In this post, I will present Google Data Studio (GDS), a data visualization tool that may be easier to learn for those who are less technical. At Fields Data, we use this tool for quick analyses, to share information with others and to make presentations.


GDS is a free tool that allows you to easily create diverse types of visualizations of data imported from Google Sheets. The types of visualizations available include maps, bar charts, pie charts and even pivot tables. This tool is especially useful when attempting to analyse data without using code. However, there are several other ways of utilizing it. Below, I have outlined a few of Fields Data’s use cases to highlight the tool’s versatility.


We utilize GDS to create quick charts that are added to newsletters, emails or LinkedIn posts. GDS charts enable us to clearly convey the meaning behind numbers when we are updating our followers on projects and trends. These charts also have the added benefit of being more visually appealing than the ones produced in Excel. On top of this, GDS allows users to customize colors and integrate logos, which in turn enables us to maintain a more cohesive brand image in our posts.

For more interactive pieces, a link to visualizations can be shared for viewing or editing, just like a Google Doc link. This removes the need to convert findings into formats that are easier to read and access, as you would do with Python-related findings.

GDS also allows us to make charts more interactive and customizable for our audience by adding filters and sliders. For example, if you have data on two countries, but your stakeholders are each interested in a different one, you can add a filter to your visualization and share it in an email. This way, each stakeholder can select their desired data without having to conduct separate analyses.

Moreover, at Fields Data we have connected our website to GDS to develop interactive charts that visitors can engage with and explore. The embedding is simple and requires minimal resources.

Example of Fields Data’s visualizations. The live version can be found at

Data Analysis

GDS’ user-friendly features make it particularly accessible for people to learn, compared to Python which can be cumbersome for those without a technical background. GDS is also maintained on Google’s cloud for easy access. As a general rule, I utilize Python when I am working on larger, more complicated data that might include varying degrees of spelling, alphanumeric data and multiple languages for instance. However, for more simple data that is of a manageable size, I recommend using GDS. Creating charts and graphs of the data will allow you to view the same insights as you would with Python, while cutting out the extra steps of having to convert the data into something easier to share with a larger audience.


Overall, GDS requires minimal investment to learn and integrate into existing workflows. The tool is intuitive and helps to uncover insights much faster than might otherwise be achieved with a coding language. Additionally, GDS allows for more user engagement using filters and sliders, more brand cohesiveness thanks to the customization of colors and logos, as well as the creation of quick visuals for posting on social media. Embedding GDS into a website is simple and low-maintenance, so if your organization is seeking a free and easy tool for data visualization and data analysis, I recommend trying it out and reading one of my previous posts on data visualization to get started.