Getty Images/iStockphoto

Looker adds customization capabilities to analytics platform

In concert with its virtual user conference, the vendor introduced the idea of composable analytics, along with tools that enable users to compose customized embeddable dashboards.

Looker has unveiled Looker Components, a set of capabilities that enable users to build customized analytics assets without having to write code.

Looker, founded in 2012 and based in Santa Cruz, Calif., unveiled the new capability Monday along with others in blog posts published in concert with JOIN 2021, the vendor's virtual user conference.

Looker Components, part of the Looker Extension Framework for application developers, forms the foundation of what the vendor is calling composable analytics.

Composable analytics, as Looker defines it, is the concept of enabling users to quickly and easily assemble their own data experiences by choosing different components and piecing them together with low-code deployment options.

For example, Looker dashboards are generally made up of three components: visualizations that display queries from the database, filters that provide an interface to interact with queries on the dashboard, and layout controls that allow users to determine the size of the visual elements on the dashboard.

Now, with visualization components and filter components, users can choose from a variety of visualization and filter options to create customized dashboards they can then embed into their workflows using the Extension Framework.

In a blog post, Kenneth Cunanan, a product manager at Looker, called visualization components and filter components the next step for the Looker analytics platform, making it possible to embed Looker data into a host of existing data workflows.

Likewise, David Menninger, an analyst at Ventana Research, noted that the introduction of composable analytics enables new personas to build customized analytics assets. Looker previously focused on trained application developers, but the vendor is targeting business users with the new capabilities.

Looker has been targeted primarily at developers who are delivering analytics to business users. With composable analytics, they are able to reach a broader, less technical audience.
David MenningerAnalyst, Ventana Research

"Looker has been targeted primarily at developers who are delivering analytics to business users," he said. "With composable analytics, they are able to reach a broader, less technical audience."

Embedded analytics, meanwhile, is gaining popularity, and Looker's focus on enabling the composition of customized embeddable assets stands to benefit the vendor's customers, Menninger added.

"Looker is well liked among those trying to support others in their use of analytics," he said. "Embedded analytics is on the rise, and we expect more than half of all analytics will be delivered in this manner. If you measure Looker in this context, they are doing the right things."

Where there's room for improvement, however, is its visualization capabilities, Menninger continued.

"If you measure Looker against end-user visualization tools, there's progress but still more work to do," he said.

Beyond the introduction of composable analytics, Looker added new augmented analytics tools, a universal semantic model, Google Data Studio as part of its analytics platform, and a new public marketplace.

New augmented analytics tools include a Looker Block for Contact Center AI (CCAI) and a Looker Block for Healthcare NLP; CCAI and Healthcare NLP are both Google Cloud capabilities, while Looker Blocks are prebuilt data models that enable users to connect to data sources and analyze data.

Customer information on a sample dashboard from Looker
A sample dashboard from Looker displays an organization's customer information.

Google Cloud is Looker's parent company after acquiring the analytics vendor for $2.6 billion in June 2019.

Looker's Block for CCAI is designed to help Looker users gain a better understanding of their customers through their own first-party data, while Block for Healthcare NLP provides a bridge between Looker and the healthcare systems and healthcare applications hosted on Google Cloud.

Looker's introduction of a universal semantic model expands on the semantic model the vendor has been built on since its inception. Its semantic model has enabled developers to define and describe their organizations' business rules and calculations with centralized semantic definitions that ensure consistent interpretations of data.

Looker, however, is now connecting to more data sources through partnerships and integrations such as its recently unveiled integration with fellow analytics vendor Tableau, and the universal semantic model enables organizations to deliver trusted and governed data across multiple tools.

Finally, Google Data Studio is designed to complement the Looker analytics platform by enabling reporting and analysis directly on top of Google Ads and other data sources, while the Looker Marketplace provides a hub for exploring analytics content such as applications, blocks and plug-ins.

"These new capabilities demonstrate that Google is committed to continuing to improve the reach and capabilities of Looker," Menninger said. "They are also competitive with where other vendors are investing, i.e., AI and natural language processing."

Next Steps

Marketing agency uses Looker to build data platform, grow

Dig Deeper on Business intelligence technology

Data Management
Content Management