Organizations focus not only on storing data but also employ Business intelligence (BI) experts to get business insights into data. But as technology has upgraded over the years, many BI tools have replaced BI experts, making it easy for organizations to create reports and data-driven decisions. One such tool is Google Data Studio, which assists organizations in generating insights with ease.
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Google Data Studio enables users to create stories about their data through dashboards and reports. Users can also share these stories by embedding the messages on social media platforms like Facebook or Twitter.
For creating reports, Google Data Studio not only allows you to connect with Google products like Google Ads, Sheets, and Analytics, but also integrates with other data sources like PostgreSQL, SQL, MySQL, and MongoDB.
In this article, you will learn how to perform a Google Data Studio MongoDB connection.
Prerequisites
Basic knowledge of the need for integrations
What is Google Data Studio?
Google Data Studio is a free, open-source tool that converts your information into easy-to-read, easily shared, and customizable reports and dashboards. With Google Data Studio, you can tell your data story with bar charts, pie charts, geo maps, bubble graphs, pivot tables, paginated data tables, and more. You can also make your reports interactive using viewer filters and data range controls. The data control feature in Google Data Studio is used to turn any report into a flexible template. Reports in Google Data Studio use links and clickable images to create product catalogs, video libraries, and other hyperlinked content.
Google Data Studio enables users to create reports on data from databases like MySQL, BigQuery, PostgreSQL, Google Marketing Platform products like Google Analytics, Google Ads, Display & Video 360, and Google consumer products like Google Sheets, Youtube, and Search Console. It also allows users to share data insights with teams, friends, colleagues, or anybody in the world. Users can invite others to edit or view their reports by sending links in emails. Google Data Studio also lets you embed your reports to other pages like Google Sites, blog posts, marketing articles, and annual reports to tell your data stories broadly.
Features of Google Data Studio
- Multiple data sources
Google Studio can analyze data from different datasets due to a wide range of database connectors. With Google Data Studio, you can import data from third-party sources like Funnel, TapClicks, Jira Cloud, Amazon Seller Central, and more.
- Interactive data visualization
The view mode of Google Data Studio is highly responsive to features like chart interaction controls, cross-charts interactions, and drill-downs. As a result, users can customize anything from filters to metrics for discovering various insights into their reports. Data Studio Explorer allows users to understand reports by using graphs and tables on small bits of data.
- Real-time collaboration
Similar to other Google’s productivity tools, you and your colleagues can work on the same Google Data Studio report in real-time. At the top of the report, a share menu invites people to work with you. With Google Data Studio, you can share your workspace with your colleagues. Their Google profile will be shown on the menu bar if they join you. Google Data Studio enables users to edit and view reports with their team members.
- Easy to use
The Google Data Studio’s user interface is easy to use, and its workspace consists of drag and drop actions for creating the report. It also consists of ready-to-use report templates for different categories. You can even add custom property panels for each object you use in reports.
- Scheduling reports
Sharing project reports with clients is an important task. Google Data Studio has a feature called Schedule email delivery, which you can use to create a report for your client and schedule a delivery. Google Data Studio can automatically notify clients when the report is due with this feature.
- Superior dashboard
Google Data Studio enables users to create dashboards using the below set of features.
- Search Data Studio box: It is the box at the top that enables users to look for reports, templates, and data sources.
- Recent section: It gives users the option to swap the visibility for reports, data sources, and explorer.
- Create: It is a left-hand side menu used to create a new report, data source, or explorer. Users can also find shared items and templates in this space.
- Gear icon: It is used for customizing user settings.
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Get started for Free with Hevo!What is MongoDB?
MongoDB is an open-source NoSQL database management program founded by Dwight Merriman, Eliot Horowitz, and Kevin Ryan in 2007. MongoDB is used to manage document-oriented data information and is mainly developed for big data applications. It stores data in documents and collections instead of rows and columns. MongoDB consists of documents containing a data structure of keys and values pairs. Since MongoDB documents are in Binary JavaScript Object Notation (BSON), they accommodate more data types for broader business use cases. These documents are in Collections – a set of documents – in MongoDB, which functions the same as tables in relational databases.
MongoDB does not require predefined schemas design like other databases. It can store any data that gives users flexibility for creating any number of fields in a document. While designing a schema, you should follow specific considerations as mentioned:
- Store the data
- Provide excellent query performance
- A reasonable quantity of hardware
One of the main features of MongoDB is horizontal scalability, which makes it an essential database for organizations running big data applications.
MongoDB supports multiple storage engines, as different engines give better performance on specific workloads. The pluggable storage engines in MongoDB can add new capabilities and configure for the optimal use of hardware. It reduces the developer and operational complexity of running multiple database technologies.
Google Data Studio MongoDB Connection
Google Data Studio MongoDB: Create reports from MongoDB data in Google Data Studio
In this tutorial for Google Data Studio MongoDB connection, you will be using CData Connect Cloud for Google Data Studio MongoDB connection to create a virtual MySQL database for accessing MongoDB data and creating custom reports in Google Data Studio.
Google Data Studio enables users to create reports with data visualizations that clients can share. When you connect Google Data Studio MongoDB with CData Connect Cloud, you can get instant access to MongoDB data for visualizations, dashboards, and more.
Google Data Studio MongoDB: Connecting MongoDB from Connect Cloud
CData Connect Cloud provides a straightforward interface for connecting Google Data Studio MongoDB.
Follow the below steps to connect MongoDB from Connect Cloud for Google Data Studio MongoDB connection.
- Sign up for a free trial at CData Connect Cloud.
- Log in Connect Cloud and click on Databases. It will show the below window.
- Select MongoDB from the available data sources.
- You need to enter the necessary authentication properties to connect with MongoDB.
The authentication properties include the server’s name, database’s name, username, and password to connect with MongoDB, as shown in the image below. You can use automatic schema discovery or write your schema definitions to access the MongoDB collections as tables. Schemas consist of a simple format and are defined in .rsd files.
- Click on the Test Database tab.
- Click on Privileges and add the user or existing user with appropriate permissions.
After creating the database virtually, you are ready for the Google Data Studio MongoDB connection
Google Data Studio MongoDB: Visualizing MongoDB data in Google Data Studio
Follow the below steps to connect CData Connect Cloud for Google Data Studio MongoDB connection.
- Log in to Google Data Studio and click on data sources.
- Create a new data source and choose the CData Connect Cloud connector for the Google Data Studio MongoDB connection, as shown below.
- You need to authorize the CData Connect Cloud connector for Google Data Studio MongoDB connection to an external service which is your Connect Cloud instance.
- You need to use your instance name, username, and password for connecting with the CData Connect Cloud instance for the Google Data Studio MongoDB connection.
- Select MongoDB database and click on Next.
- Select a Table and click on Next.
- Click on Connect, as shown in the below image. this will initiate the Google Data Studio MongoDB connection.
- Click on create Report and then add a data source to the Report below.
- Select the visualization style and add it to the report.
- Select the dimensions and measures for customizing your visualization as shown below.
Therefore, you have used the CData Connect Cloud instance for Google Data Studio MongoDB data visualization. You can also use MySQL connector to use custom SQL queries for visualization and Google Data Studio MongoDB connections.
Conclusion
In this article, you have learned about Google Data Studio MongoDB connection using CData Connect Cloud. Google Data Studio can be used to visualize databases like PostgreSQL, MySQL, and SQL.
Google Data Studio can also be used with Amazon Redshift and Google BigQuery data for visualizations. Third-party applications like Supermetrics, CData Connect, Onlizer, and more allow users to connect Google Data Studio with storage devices like Amazon S3 and JSON data.
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