Google Data Studio Tutorial for Beginners
The Google Data Studio tutorial to create a simple dashboard, as well as discover basic concepts, such as data sources, connectors, metrics, and dimensions
Google Data Studio is a tool that enables users to easily create and share visually appealing dashboards and reports. It is user-friendly, but can be intimidating for those who are new to it. This tutorial aims to provide a comprehensive guide on how to use Google Data Studio, starting with creating a dashboard and covering other essential features such as sharing reports. By following this tutorial, you will be able to master the basics of Google Data Studio and create professional-looking dashboards with minimal effort.
What is Google Data Studio?
Google Data Studio is a data visualization and reporting tool offered by Google as part of its suite of cloud-based productivity tools. It allows users to create interactive, customizable dashboards and reports using a variety of data sources, including Google Sheets, Google Analytics, and other third-party data connectors. With Google Data Studio, users can easily transform raw data into clear and concise visualizations, such as charts, tables, and maps, which can be used to track and analyze trends, identify patterns, and monitor performance.
One of the key benefits of Google Data Studio is its ability to integrate with various data sources, making it easy for users to pull in data from a wide range of sources and create a single, comprehensive dashboard. In addition, Google Data Studio offers a range of formatting and styling options, allowing users to create visually appealing and professional-looking dashboards and reports. It is a powerful tool that is widely used by businesses, organizations, and individuals to better understand and communicate their data.
Google Data Studio comes with a variety of pre-built templates that make it easy for users to create professional-looking dashboards with a wide range of charts and visualizations. These templates provide a convenient starting point for users to customize and build upon, saving time and effort in the dashboard creation process. With just a few clicks, users can add and configure charts, tables, maps, and other visualizations, and arrange them on the dashboard to create a cohesive and informative report. Overall, the pre-built templates in Data Studio make it fast and simple to create beautiful dashboards full of charts and other data visualizations
Google Data Studio is a cloud-based tool, which means that it can be accessed from any device with a web browser and an internet connection. This makes it convenient for users to access their dashboards and reports from any location, as long as they have an internet connection. In addition, all reports created in Data Studio are automatically saved to Google Drive, providing users with a safe and reliable storage solution.
One of the key advantages of Data Studio is its ability to connect and integrate with a variety of data sources, allowing users to analyze and present data from multiple sources in a single dashboard or report. This makes it easy for users to get a comprehensive view of their data and identify trends and patterns across different datasets. Data Studio is also user-friendly, with a simple and intuitive interface that does not require any programming skills to get started. Overall, Data Studio is a powerful and accessible tool that enables users to easily connect, analyze, and present data from multiple sources.
How to use Google Data Studio?
To begin using Google Data Studio, you will need to sign in with a Google account. If you do not already have a Google account, you can create one for free. Once you have signed in, navigate to https://datastudio.google.com to access the Data Studio home screen. From this screen, you can create a new report, access existing reports, and explore the various features and resources available in Data Studio.
The Google Data Studio home page is composed of several key parts:
The left menu: This menu provides quick access to options for creating new reports, data sources, or explorers, as well as accessing reports that have been shared with you or created by you. It also includes a trash folder for deleted reports.
The toolbar menu: This menu allows you to access all of your reports, view all of your data sources, and explore or tweak a chart without modifying the report.
The search bar: This bar is located at the top of the page and allows you to search for reports by name.
The Template Gallery: This area provides a selection of pre-made templates and a blank report that can be used to create a new dashboard. The Template Gallery can be accessed by clicking "Template Gallery" in the top-right corner of the area.
The report list: Located just below the Template Gallery, the report list allows you to sort your reports by name, owner, or last opened date.
Overall, these features of the Data Studio home page provide users with a convenient way to navigate and manage their reports and data sources.
Google Data Studio: Data sources and connectors
Google Data Studio allows users to connect to a variety of data sources and integrate the data into their dashboards and reports. A data source is a source of data that is used to populate the charts and visualizations in a Data Studio report. Data sources can be either Google products (such as Google Sheets, Google Analytics, etc.) or third-party data sources (such as MySQL databases, CSV files, etc.) that can be connected to Data Studio using connectors.
Connectors are tools that enable Data Studio to connect to and retrieve data from external data sources. Google offers a range of built-in connectors for popular data sources, such as Google Sheets, Google Analytics, and Google BigQuery. In addition, Data Studio also supports a range of third-party connectors that can be used to connect to other data sources, such as MySQL databases, Salesforce, and more.
To use a data source in a Data Studio report, users first need to create a connection to the data source using a connector. This can be done by clicking on the "Create" button in the left menu and selecting "Data Source" from the dropdown menu. From there, users can select the type of connector they want to use and follow the prompts to create the connection and configure the data source. Once the connection has been established, users can use the data source to populate their charts and visualizations in the report.
You can see the full list of available connectors here.
Google Data Studio: Metrics and dimensions
In Google Data Studio, metrics and dimensions are terms used to describe the data that is used to populate charts and visualizations.
Metrics are numerical values that are used to measure and track performance. Examples of metrics include revenue, number of clicks, pageviews, and average order value. Metrics are typically used to track changes over time and can be plotted on charts as a line, bar, or area.
Dimensions, on the other hand, are non-numeric values that are used to describe and classify data. Examples of dimensions include location, device type, and page title. Dimensions are typically used to slice and dice data and can be used to filter and group data in charts.
In Data Studio, metrics and dimensions are used together to build charts and visualizations. For example, a line chart showing the number of pageviews over time might use the "Date" dimension to plot the data on the x-axis and the "Pageviews" metric to plot the data on the y-axis. By using different combinations of metrics and dimensions, users can create a wide range of charts and visualizations to help them understand and communicate their data.
To further illustrate the concept of metrics and dimensions, let's consider an example where you want to create a dashboard to track the sales of your products. Some possible metrics that you might want to include in your dashboard are:
- Sales revenue: This metric could be used to track the total revenue generated from selling your products online.
- Number of customers: This metric could be used to track the number of customers who have purchased your products.
- Maximum sales: This metric could be used to track the highest sales value for a particular product or time period.
- Minimum sales: This metric could be used to track the lowest sales value for a particular product or time period.
- Average product price: This metric could be used to track the average price of your products.
To analyze your data from different angles, you could use dimensions such as:
- Sales per month: This dimension could be used to break down your sales revenue by month, allowing you to see how your sales have changed over time.
- Sales per order type: This dimension could be used to differentiate between different types of orders, such as wholesale orders versus retail orders.
- Customer country of origin: This dimension could be used to track the geographical location of your customers.
- Customer age, gender, and device type: These dimensions could be used to gain a deeper understanding of your customer demographics.
- Product name: This dimension could be used to track the sales performance of individual products.
- Day of the week: This dimension could be used to see how sales vary by day of the week.
- Product type: This dimension could be used to track the sales performance of different product categories.
By using a combination of metrics and dimensions, you can create a range of charts and visualizations that allow you to understand and analyze your data from multiple perspectives.
Create a dashboard in Google Data Studio
Before you create a dashboard in Google Data Studio, there are a few things you should consider:
Determine your goals: The first step in creating a dashboard is to define your goals and objectives. What do you want to achieve with your dashboard? What information do you want to communicate? Having clear goals will help you focus on the most important data and visualizations for your dashboard.
Choose your data sources: Once you have defined your goals, you will need to decide on the data sources that you want to use in your dashboard. This may include Google products such as Google Sheets or Google Analytics, as well as third-party data sources that can be connected to Data Studio using connectors.
Identify the metrics and dimensions you want to use: Based on your goals and data sources, you will need to decide on the metrics and dimensions that you want to include in your dashboard. This will involve selecting the numerical values (metrics) that you want to track and the non-numeric values (dimensions) that you want to use to describe and classify your data.
Choose a template or create a blank report: Data Studio offers a range of pre-made templates that can be used as a starting point for your dashboard. Alternatively, you can create a blank report and build your dashboard from scratch.
Plan your dashboard layout: Before you start adding charts and visualizations to your dashboard, it can be helpful to plan out the overall layout and design of your dashboard. This will involve deciding on the size and position of each element, as well as the overall look and feel of the dashboard.
1. Prepare the dataset (we’ll use Google Sheets)
In this tutorial, we will be using Google Sheets as our data source for Google Data Studio. There are several reasons why we choose to use Google Sheets:
- Google Sheets is widely available and easy to use, even for beginners.
- Google Sheets files are stored on Google Drive, which makes them accessible from any device with a Google account.
- Google Sheets allows users to read and import data from various file types, including CSV files and Microsoft Excel spreadsheets.
- Google Sheets can be easily connected to other Google services, making it easy to import and combine data from multiple sources.
To follow along with this tutorial, you will need to make a copy of a provided spreadsheet file containing online sales data. To do this, open the file in Google Sheets and click on "File > Make a copy" to save the file to your Google Drive. You can then use this file as the dataset for your dashboard in Google Data Studio.
2. Prepare the dashboard layout
Before you start building your report in Google Data Studio, it is a good idea to take some time to design the layout and overall structure of your report. This can help you avoid getting stuck or feeling overwhelmed as you build your dashboard.
To design your report, consider the following:
- What information do you want to present in your report?
- What charts and visualizations will you use to display this information?
- How will you arrange the charts and visualizations on your dashboard?
A rough sketch of your report layout can be helpful in this process. You can use a pen and paper or a digital tool to create your sketch. This will give you a visual representation of how your report will look and help you identify any potential issues or areas for improvement.
It can also be useful to ask potential viewers of your report what information they want to see. This can help you ensure that your report is focused on the most important metrics and provides easy-to-digest information that is relevant to your audience.