Embedded Analytics is aimed at bridging this gap. It helps an organization create unified User Experiences for their decision-makers by allowing them to access the internal business process applications and Dashboards from one place.
A popular Web-based Business Intelligence platform that is used by a large number of businesses is Looker. It also houses support for Looker Embedded Analytics.
Through Looker Embedded Analytics, an organization can bring Looker features to their internal applications, build custom applications using Looker API or even rebrand Looker as their internal application via White Labeling.
Introduction to Looker
Looker is a Business Intelligence tool that gives organizations the ability to explore data and build visualizations to make data-driven business decisions.
Looker is available as a completely managed online solution or as an application that can be deployed On-premise.
Looker’s ability to connect to most of the Cloud-based as well as On-premise data sources makes it a favorite among organizations that use a mix of these services.
In the case of On-premise data sources, Looker can create a secure channel that ensures Data Security.
Image Source: https://looker.com/platform/overview
Looker houses a Data Modeling layer which is separate from the components that help visualize data. The functionalities offered by this layer can be leveraged by developers to transform data, perform numerous join operations across tables, etc., which can then be used by the business teams to perform the necessary analysis.
This functionality is considered to be extremely important as it allows multiple developers to work parallelly on a model and merge their work with Github Sync.
Understanding the Key Features of Looker
The key features of Looker are as follows:
- Modern Business Intelligence: Since Looker provides access to reliable and up-to-date data, it can be used to create real-time dashboards for an in-depth and consistent analysis resulting in more precise reporting.
- Custom Applications: Looker gives users the ability to create custom applications that can deliver unique data experiences suited to each business. Looker also houses numerous embedded analytics solutions that provide users with the data they need to perform all necessary tasks.
- Advanced Integrations: Looker supports seamless integration with Google BigQuery, Snowflake, AWS Redshift along with 50+ SQL dialects. This gives users the ability to link with multiple databases, avoid database lock-in, and maintain multi-cloud data environments.
- Advanced Hosting: Looker supports hosting on public Cloud-based platforms such as Google Cloud Platform (GCP) or Amazon Web Services (AWS) along with other multi-cloud and hybrid environments.
Understanding Looker Embedded Analytics
Looker Embedded Analytics can be implemented using one of the four following ways:
- Private Embedding: By providing access to Looker through an internal application by a separate Looker login.
- Public Embedding: By enabling access to Looker without a separate Looker sign-in.
- Custom Applications: By building custom applications using Looker APIs.
- White Labeling: By creating a rebranded Looker platform for your organization.
It can be observed that the last two methods for setting up Looker Embedded Analytics are a bit more complex and cannot be executed without a dedicated development team. Embedding Looker Analytics features into your applications through Public or Private Embedding is fairly simple and can be accomplished quickly.
Steps to Set up Looker Embedded Analytics
The basic premise of setting up Looker Embedded Analytics is to have access to a custom application. This example will be making use of a simple HTML page as the custom application. The code for the HTML page is as follows:
<!DOCTYPE html>
<html>
<head>
<title>View Customer Complaints</title>
</head>
<body>
<h1>Customer Complaint Dashboard</h1>
<h3>Top Issues</h3>
<div id=”demo-dashboard-area”>
<div id = “dashboard”>
</div>
</div>
</body>
</html>
The div tag marked as demo-dashboard-area is where you will try to set up Looker Embedded Analytics.
Looker Embedded Analytics Step 1: Before embedding the URL, you need to let Looker know that such an application will try to access the Looker Dashboard. This is because Looker’s default behavior is to reject all such requests from external applications. To get around this, add the URL of your web application in the Embedded Domain whitelist section. Also, ensure that the Same-Origin Protection in Looker is disabled.
Looker Embedded Analytics Step 2: Now head to your Looker instance and click on the Dashboard that you want to embed within your Web Application. Copy the URL from the browser top bar and paste it inside the div tag named dashboard as an iframe tag as shown below.
<!DOCTYPE html>
<html>
<head>
<title>View Customer Complaints</title>
</head>
<body>
<h1>Customer Complaint Dashboard</h1>
<h3>Top Issues</h3>
<div id=”demo-dashboard-area”>
<div id = “dashboard”>
<iframe src=”LOOKER_DASHBOARD_URL””></iframe>
</div>
</div>
</body>
</html>
That is the simplest method that can be leveraged to set up Looker Embedded Analytics. A caveat here is that this web application instead of directly displaying the dashboard will first take users to the Looker login page. This is because this process makes use of the Private Embedding method.
If you want to make the User Experience even smoother, you can implement the Public Embedding method, which requires you to use the Looker SDK and a Secret API Key generated from the Looker Admin portal.
The idea is that if this Secret Key is passed along with the request to Looker, it allows one to display the Dashboard without logging in. This also means that you will need more involved development to handle the Secure Storage and the Secret Key.
Conclusion
Looker Embedding Analytics feature allows organizations to create a smooth User Experience by letting them have access to the Dashboards from within the internal applications.
Having this ability reduces development costs and helps build custom applications faster. This is one of the most powerful features that make Looker a favorite among organizations.
That said, Looker does have its share of weaknesses. If there is one weakness in the otherwise decorated feature set, it is that Looker’s ability to integrate with different types of data sources is still not comprehensive.
Vivek Sinha is a seasoned product leader with over 10 years of expertise in revolutionizing real-time analytics and cloud-native technologies. He specializes in enhancing Apache Pinot, focusing on query processing and data mutability. Vivek is renowned for his strategic vision and ability to deliver cutting-edge solutions that empower businesses to harness the full potential of their data.
