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Editorial

Google's Winning Business Intelligence Pieces: Looker and BigQuery SQL

6 minute read
Pierre DeBois avatar
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. 

Learning Opportunities

Now with BigQuery, analysts can create and run Apache Spark from stored procedures. The result is a consolidated workflow for analysts and data scientists who want to read from a data warehouse or a data lake built on BigQuery. Plus, these procedures can be created in popular languages for data such as Python, streamlining requests and making model development simpler. That can help marketers who need to explore advanced analysis such as cohort analysis and predictive models.

Users can also collaborate on BigQuery from other integrated developer environments (IDEs). For example, by using Google Colab users can run Python along with BigQuery.

Related Article: Defining Your Marketing Technology Philosophy

Marketing Data Strategy Is Emphasizing the 'Tech' in Martech

The introduction of BigQuerySQL essentially provides Google another IDE to compete against the likes of Posit RStudio and Microsoft Visual Studio Code. Both of those IDEs are more familiar to developers and programmers, and BigQuery has long been a back-end application in the developer space. But Google integrations have evolved BigQuery into more of a business staple, one which marketers are increasingly seeing in their daily assignments. This makes Apache Spark integration have more business appeal in BigQuery, while placing it in square competition with other technical IDEs or solutions that support SQL query capabilities.

The adjustment reflects how data has transformed from being a technical resource to a strategic marketing asset. Originally operations managers relied on data in statistical applications to ensure that performance concerns were monitored. Marketers soon found themselves among users learning how to use SQL and access data lake platforms like BigQuery more frequently, the operational concerns becoming more of a part of core business lines and strategic models. For example, Google cited how retailer Mercado Libre and marketing agency Wpromote rely on Looker and BigQuery. These instances reflect how marketers are finding themselves increasingly examining data integration in advanced tools to provide customer experience insights. 

The Looker and BigQuerySQL introductions arrive just as solution integration and martech utility are becoming hot marketplace topics. Marketers are seeing increased data needs while becoming increasingly overwhelmed to use their martech solutions to full utility, hampering speedy data-centric decision making and building customized data models.

Recent industry surveys are divulging that struggle sentiment. A marketing budget survey developed jointly by the Content Marketing Institute, ON24 and MarketingProfs revealed that only 28% of surveyed B2B marketers felt they had "the right technology in place" and only 31% thought that technology was being "properly utilized." A Gartner Marketing Technology Survey noted that respondents utilize just 42% of the capabilities in their martech stack.

The Looker and BigQuery product changes add another valuable business intelligence integration in the marketplace. With Looker Studio and BigQuery SQL, Google will surely keep the "Jenga pieces" of business intelligence from falling apart.

About the author

Pierre DeBois

Pierre DeBois is the founder of Zimana, a small business digital analytics consultancy. He reviews data from web analytics and social media dashboard solutions, then provides recommendations and web development action that improves marketing strategy and business profitability.

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