Google Updates Business Intelligence Solutions with Looker and BigQuery SQL

Google’s new product changes add another valuable business intelligence integration in the marketplace. The best business solutions are like Jenga pieces — you need the right pieces to hold the stack together. Solution providers are constantly working to find the right “Jenga pieces” for their business intelligence offerings. One provider, Google, […]

Google’s new product changes add another valuable business intelligence integration in the marketplace.

The best business solutions are like Jenga pieces — you need the right pieces to hold the stack together.

Solution providers are constantly working to find the right “Jenga pieces” for their business intelligence offerings. One provider, Google, seems to have pulled together the right stack.

Google announced a realignment of its cloud solutions under a new sub-brand called Looker. Google Data Studio is now called Looker Studio, and Google is introducing a paid version called Studio Pro for enterprise data needs.

What Is Google’s Looker Studio?

Looker Studio is a continuation of Data Studio, offering the same features that have been available under the old moniker — and new ones such as Data Blending, which I covered here. This keeps its purpose unchanged: a user-friendly visualization canvas that integrates data from Google platforms such as Google Ads, Google Analytics and Google Search Console. The home page remains the starting point for creating and accessing all your Looker Studio assets: reports, data sources and explorations. This also means the same user interface features that connect to various data sources remain free, too.

The URL where you log in into your account has been updated to reflect the new name — lookerstudio.google.com — as well as the help center URL. When I logged in to my account, I saw that everything looked the same, save for the new Looker logo in the upper left of the screen.

looker studio

With Looker, Data Studio marks its evolution beyond its 2016 introductory roots as an analytics supplementary dashboard. In a post announcing Looker, Google notes that Data Studio supports over 800 data sources with 600 connectors. That amount of support means data layer updates must go beyond dashboard tasks into more sophisticated real-time visualizations to be valuable to users.

Looker Studio Pro, on the other hand, is new. It is a dedicated version for advanced enterprise management needs such as team collaboration and service level agreements (SLAs), much like Google Analytics 360. Like that analytics platform, Looker Studio Pro offers dedicated features for enterprise users.

Two new features are team workplaces and Google Cloud project linking. Team workspaces is a collaboration interface appearing alongside the user interface to assist team discussion around the data visualization in their Data Studio project. Each team member with a workspace is given a specific permission based on a granted role: manager, content manager or contributor. Google project linking provides a permission workflow so that reports and data sources remain in an organization’s access, rather than solely to an individual. This allows critical assets to continue to function even if the team member who created them leaves the organization.

Google will continue to refine Looker Studio with integration enhancements. The first beta is a Google sheets integration, expected to roll out of beta in 2023. On its website, Google noted other source connections such as Tableau and Power BI. These arrive as Google had earlier introduced a Google Analytics 4 connector for Looker Studio.

Related Article: Expert Tips for Taming the Martech Madness

Google’s Other Business Intelligence News: BigQuery SQL

This is not the only consolidation Google has announced. In recent months it combined two of its data platforms: BigQuery and Apache Spark. The combined platforms are now called Google BigQuery SQL.

The combination expands the capability of using BigQuery procedures with other data models. BigQuery procedures are a stored collection of statements that can be called from queries or procedures to bring data together. Apache Spark is often applied in exploratory analysis projects, ranging from ad-hoc data analysis to machine learning models. 

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