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Custom data visualization with Looker

How individual extensions enable complex data visualization

The business intelligence tool Looker enables dynamic data analysis that empowers companies to make data-based decisions. Although semantic data modeling is excellently covered by Looker, we reached limits in data visualization for individual requirements. We therefore tested additional extensions for data visualization in an application example: While the data is still cleanly retrieved from the Looker backend via the API, we shook off all limitations in the frontend - and still placed the familiar Looker dashboard next to it.

Data-based decisions as the key to success

No decision without clean data: Data quality has long since become a success factor for companies. However, it is a major challenge to prepare data in such a way that employees are empowered to make decisions. With the help of Looker, data can be modeled via an intermediate data-level in such a way that non-technical personnel are able to independently ask and answer questions using data. Good modeling allows staff to confidently handle granular data without having to know where exactly the data comes from, how to address it, and without fear of making mistakes. The intermediate data layer lies between the raw data from the database and the user dashboards. On this level, it is determined who is allowed to see which data and how the data may be used. The users thus simultaneously get coherent access to relevant data, can individually design their own dashboards and still all use the same data - there is a single source of truth.

With a data model in Looker, employees are empowered to make data-based decisions without having to contact data analysts. Looker enables companies to democratize data and empowers decision makers to provide answers to complex questions.

Data is accessible specifically for individual, technical questions via the "Explore" layer. For common questions, the data is accessible primarily through dashboards, which is an overview of visually prepared data according to predefined building blocks. For both levels, visualizations that take place outside of Looker can be interesting. For example, for visualizations that are to process very large amounts of data or many data points.

More information about the benefits of Looker can be found here

Visualization of multidimensional data with Looker

The Looker dashboards provide an extensive database of visualization options. In addition, Looker already offers many out-of-the-box solutions, and others can be added via the Marketplace or built within the Looker framework itself. However, even these options have their limits when it comes to full customization. 

In order to use the full design freedom for visualization on a map, Looker offers additional extensions. With the Looker SDK, the Looker application can also be integrated into your own applications. The clean data is obtained from the Looker backend via the API, but the own front-end application can be designed individually. 

This allows you to remove the following limitations of the default settings and build solutions that:

  • Display multidimensional data on the map
  • Provide full design freedom in visualization on the map
  • Display larger data point sets
  • are flexible in the choice of map provider

Application example: Looker data visualization in your own application

  • interconnected custom map and looker data module
  • The data is filtered on the custom map as well as in the Looker dashboard

Using the Looker Embed SDK, we embedded Looker as an iframe in our own application. As experts for map applications in Hamburg, we took on the data visualization of ship data in the port of our hometown on a map. 

In our example we use a map from Google Maps, but the map provider can be chosen flexibly as opposed to the default mapbox setting in Looker. The map and the Looker dashboard are synchronized with each other to create interactivity. The controls of the map such as slider, date selection or filters are adapted to Looker's design, so the interface of our map application and the embedded Looker dashboard are similar. Thanks to synchronization, the map solution works like a unified Looker application.

On our map, multiple properties such as position, speed and type of vessel can be visualized simultaneously. Two different data sources are included. With a heatmap, we provide another individual visualization on the map.

Your own application with data from Looker

Ultimately, the data from Looker can also be reproduced in a completely individualized form via a custom application. The programming effort is correspondingly high, since the own application is developed by the user. The data is extracted via the Looker API and prepared in the user's own design. Although the visualization of Looker is not used, you still benefit from the the data modelling of Looker.

Flexible data visualization with business intelligence tools

Looker already offers a wide range of visualization options in the standard settings. With the extended options, we address complex issues and special requirements, but always rely on Looker's data modeling and data interface. Our application example is meant to show which visualizations - especially on the map - are possible if you remove the limitations of the standard settings.

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