Data Studio is use for data visualization and as a reporting tool. It was created by Google in 2016. And it has gained a lot of traction from Data Scientists, Analysts, and Sales and Marketing Experts.

Data Studio is completely free. There’s no paid version of it. You can use it as an alternative to paid reporting tools such as Tableau and Power BI.

Data Studio is cloud-based:

It’s accessible through any browser and an internet connection. The reports you create are saved automatically into Google Data Studio framework, so they’re available anytime and anywhere. No worries about losing the files.

There are many pre-built templates in Data Studio, allowing you to create beautiful dashboards full of charts quickly and easily. It’s very easy to share reports and dashboards with your internal / external teams if they have a Google account. It enables collaboration within business groups.

With Data Studio, you can connect, analyze, and present data from different sources. You don’t even need to be tech-savvy or know programming languages to get started with Data Studio.

Google Data Studio: Data sources and connectors:

Every time you want to create a report, first, you’ll need to create a data source. It’s important to note that data sources are not your original data. To clarify and avoid confusion, see the explanation below:

• The original data, such as data in a Google spreadsheet, MySQL database, LinkedIn, YouTube, or data stored in other platforms and services, is called a dataset.
• To link a report to the dataset, you need a data connector to create a data source.
• The data source maintains the information of the connection credential. And it keeps track of all the fields that are part of that connection.  
• You can have multiple data sources connected to a dataset, and this may come in handy when collaborating with different team members. For example, you may want to share data sources with different connection capabilities for different team members.

When Data Studio was first released, there were only six Google-based data sources you could connect to. But a lot has changed since then! 

As of this writing, there are 400+ connectors to access your data from 800+ datasets. Besides Google Connectors, there are also Partner Connectors (third-party connectors). 

In the example below we’ll go through US Office Equipment Sample Dataset to visualize different charts representing the data.

• Open Google Data Studio from your browser by using this link.
• Click Create button on the left
• Open a connection to the data source of interest. In our case, we’ll use this link to the CSV file Dataset.

File Upload / Locate File:

• Upload CSV file
• On the next screen, you will be presented with a data file schema for the uploaded CSV file.
• The data types can be changed on existing fields within the data file schema and new calculated fields added if needed.

CSV files are called Unmapped data because their contents are unknown in advance.

Analyze and Visualize the Data:

• Add the data source and you will end up in the report canvas.
• Use the appropriate charts from the Add Charts tool bar menu above to select the desire charts as shown below to create data visualization reports.

Quick Steps to Set Up Data Visualization on Google Data Studio:

1. Open Data Studio.
2. Familiarize yourself with the dashboard.
3. Connect your first data source.
4. Create your first report.
5. Add some charts.
6. Customize the formatting and add a title and captions.
7. Share the report.

Conclusion:

Congratulations! We just went through how to create a Business Intelligence BI dashboard using Google Data Studio for visualizing and exploring a sample Office Equipment dataset.

Data Studio allows you to create beautiful dashboards full of charts quickly and easily. It’s very easy to use for sharing reports and dashboards with your internal/external teams if they have a Google account. It enables collaboration within business groups.

With Data Studio, you can connect, analyze, and present data from different sources. You don’t even need to be tech-savvy or know programming languages to get started with Data Studio.