Various online platforms are trying to enhance the user experience by offering their services through mobile applications. Tracking the performance of these applications is an integral part in improving their performance and the user experience of the services. Firebase provides the functionality to host backend databases of applications to ensure a similar experience on a wide variety of devices. Google Data Studio is an analytics platform that users can leverage to convert raw Firebase Analytics data into informative reports.
In this article, you will learn about Firebase, Google Data Studio, and their key features, 2 methods to implement Firebase Data Studio integration, along with some limitations.
Table of Contents
Introduction to Firebase
Firebase is a Backend as a Service [BaaS] offering Google Cloud-based app development platform. It is a Real-Time Database in which applications connect with each other using WebSockets. Under this method, all of the data synchronizes automatically through a single WebSocket depending on how fast the internet connection can transmit it. It also provides the functionality to store binary files directly from the client onto the Cloud platform. Developers can use Firebase to integrate OAuth from Google, Facebook, Twitter, and GitHub to incorporate authentication for users of an application. It provides an option to host static files which it serves from Global CDN with HTTP/2.
Official documentation regarding Firebase can be found here.
Key Features of Firebase
- Integration with Dynamic Links: These links help in providing enhanced functionality within apps by taking users to specific content.
- App Indexing: It supports the ability for the options for App Indexing and thus enables tracking aspects like re-engagement with different elements of the app which affect the Google App Results ranking.
- Notifications on Apps: Push notifications can be managed to perform information campaigns. These notifications are free and can be tracked using Firebase Analytics.
- Cloud Messaging for Users: Cloud Messaging allows for a more reliable way to communicate between platforms.
- Remote Configuration: Using Remote Configuration Developers can make the changes on the application on the go.
Introduction to Google Data Studio
Data Studio is a reporting tool offered by Google that helps users create custom data visualizations and real-time Dashboards using multiple data sources. This platform provides multiple connectors to establish connections with different data sources. There is also the availability of tools to present the data graphically using bar charts, line graphs, etc. It lets users expand their reports according to their needs.
Users can further establish a live connection to multiple data sources thus enabling the creation of Live Reports and Dashboards.
Official documentation regarding Google Studio can be found here.
Key Features of Google Data Studio
- Blending Data: It provides users with the functionality to blend the data from multiple sources. This will help form a complete picture of the scenario.
- Useful Filters: Users can apply filters to control the segments of data and help focus on the important parts.
- Control on Data: The platform lets users choose to view the data relevant to them rather than creating separate reports for each use case.
- Real-Time Connection: The built-in connectors offered, connect with live data sources and stream data in Real-Time or based on the frequency set by the user.
- Ease of Collaboration: It allows users to share reports with multiple people and the ability for multiple users to collaborate on a project in real-time.
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- Active Firebase Account.
- Set up of a Firebase project.
- Active Google Data Studio Account.
- Working Knowledge of Google Data Studio and Firebase.
Procedure for Firebase Data Studio Integration
Method 1: Firebase Data Studio Integration using Google BigQuery
For manually implementing a Firebase Data Studio Integration using Google BigQuery Cloud Data Warehouse platform you will be required to carry out following procedures:
Firebase Data Studio Integration Part 1: Connect a Firebase Project to Google BigQuery
Step 1: Firstly, you will have to sign in onto your Firebase project.
Step 2: Then open your Project Settings from the options menu.
Step 3: Project Settings Page will open up, proceed to open up the Integrations Tab.
Step 4: Choose the BigQuery Card and click the “Link” option.
Step 5: You will be required to enter the credentials to complete the connection.
Firebase Data Studio Integration Part 2: Selection of Apps to be Connected with Google BigQuery
Step 1: Similar to setting up the initial connection, you will need to sign in into your Firebase account.
Step 2: Proceed to selection of Project Setting options and subsequently Integrations Tab on the Project Setting page.
Step 3: You need to select the BigQuery Card and click on “Manage”.
Step 4: You can make the selections of the Applications using the toggle next to them on their respective cards.
Step 5: This toggle selection will be responsible for deactivating export of the App Data. After performing selections proceed to confirm by clicking on “Stop Exports”.
Firebase Data Studio Integration Part 3: Connecting Google BigQuery to a Google Data Studio Account
Step 1: Firstly, Sign-in into your Google Data Studio account.
Step 2: You will be required to click the Plus Sign on the top left of the window and subsequently select Data Source.
Step 3: In the drop down menu, select Google BigQuery connector.
Step 4: You are then required to provide the credentials for the connection.
Step 5: To complete the connection, click on the “CONNECT” button on the top right corner. The Data Source window will pop up and the data source connection will be established.
Firebase Data Studio Integration Part 4: Selection of Data Being Imported
Step 1: To import specific data from Google BigQuery the user will be required to implement Custom Queries while setting up the connection.
Step 2: Custom Query option provides functionality to extract and import data using a SQL Query instead of importing a complete Table.
Step 3: You will be required to enter your “Override Billing Project ID” to implement Custom Queries with query parameters of your choice.
Step 4: Then you can proceed to enter your query, you can write the queries in both the Standard SQL Dialect and the BigQuery SQL Dialect.
Official Documentation regarding query parameters can be found here.
Limitations of using Google BigQuery for Firebase Data Studio Integration
Following are the limitations that users can face while manually implementing Firebase Data Studio Integration through Google BigQuery.
- You will be required to separately manage Google BigQuery Cloud Data Warehouse which will incur additional fees.
- You will be separately implementing the two platform integrations with Google BigQuery which could lead to data not being implemented in real-time.
- The data from multiple applications can be difficult to analyze separately while importing from Google BigQuery Data Warehouse.
- Implementation of Customer Queries can get complex while integrating with multiple applications.
Method 2: Firebase Data Studio Integration using Hevo
Hevo is a No-code Data Pipeline. It supports pre-built data integrations from 100+ data sources, including 30+ Free Sources like Firebase. Hevo offers a fully managed solution for your data migration process to Google Data Studio. It will automate your data flow in minutes without writing any line of code. Its fault-tolerant architecture makes sure that your data is secure and consistent. Hevo provides you with a truly efficient and fully automated solution to manage data in real-time and always have analysis-ready data at Google Data Studio.
Hevo focuses on three simple steps to get you started:
- Connect: Connect Hevo with Frirebase and all your data sources by simply logging in with your credentials.
- Integrate: Consolidate your data from several sources in Hevo’s Managed Data Integration Platform and automatically transform it into an analysis-ready form.
- Visualize: Connect Hevo with your desired Reporting tool such as Google Data Studio and visualize your unified data easily to gain better insights.
Let’s look at some salient features of Hevo:
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- Fully Managed: It requires no management and maintenance as Hevo is a fully automated platform.
- Data Transformation: It provides a simple interface to perfect, modify, and enrich the data you want to transfer.
- Real-Time: Hevo offers real-time data migration. So, your data is always ready for analysis.
- Schema Management: Hevo can automatically detect the schema of the incoming data and maps it to the destination schema.
- Live Monitoring: Advanced monitoring gives you a one-stop view to watch all the activities that occur within pipelines.
- Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support call.
In this article, you learned about Firebase, Google Data Studio and their Key Features, 2 methods to implement Firebase Data Studio integration, and the limitations of using the manual method. You can also check Firebase BigQuery Integration.
Integrating and analyzing data from a huge set of diverse sources can be challenging, this is where Hevo comes into the picture. It helps transfer data from Firebase to a destination of your choice for free.
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Hevo Data, a No-code Data Pipeline helps you transfer data from a source of your choice in a fully automated and secure manner without having to write the code repeatedly. Hevo with its strong integration with 100+ sources & BI tools, allows you to not only export & load Data but also transform & enrich your Data & make it analysis-ready in a jiffy.
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