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Top 5 Marketing Benefits You Need to Know: Google’s Acquisition of Business Intelligence Platform Looker

DELVE Experts   
June 13, 2019  4min. read
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In an exciting move for business intelligence, Google acquired leading intelligence & analytics platform Looker this week. Thomas Kurian, CEO of Google Cloud, summarizes the strategy behind this powerful acquisition: “The combination [of Google Cloud Platform and Looker] provides an end-to-end analytics platform to connect, collect, analyze and visualize data across Google Cloud, Azure, AWS, on-premises databases and ISV applications.”

Google’s acquisition of Looker will not only drive better integrated, more efficient, and increased accessibility for marketing data management — it will help marketers make real marketing impact with a sophisticated solution that:

  • Better visualizes marketing data for clear and actionable insight
  • Ties together disparate data sets for a single source of truth
  • Unifies data definitions across all data sources for easier and more accurate analysis
  • Makes better sense of data sets for highly visual, interactive, embedded analytics
  • Reduces time to launch for more efficient marketing programs

Read on to learn more about how these top 5 benefits will help improve marketing efficiency for Google Cloud Platform customers.

  1. Looker fills the visual business intelligence gap in Google Cloud Platform
    Better visualize marketing data for clear and actionable insight

    Google Cloud Platform offers 100+ amazingly robust, scalable, and industry leading products for predictive analytics in the cloud, but none of these current products provide the visual business intelligence functionality that Looker’s uniquely powerful data analytics platform brings to the table. Google’s closest offering to date for visual business intelligence is Data Studio, which seamlessly integrates with both Google Cloud Platform and Google Marketing Platform for basic data visualization. Looker helps marketing teams explore, visualize, and share data without needing to know data programming languages like SQL. Looker will replace Data Studio’s basic data visualization offering with robust visual business intelligence and will help marketers drive deeper marketing insight in a sophisticated, integrated, and easy to use platform.

  2. Looker supports marketers’ complex data warehousing needs
    Tie together disparate data sets for a single source of truth

    Looker will be integrated into Google Cloud Platform to extend the power of BigQuery, which is Google’s industry-leading, fully managed, and highly scalable data warehousing tool. Looker while also unlock integrative power with over 35 other data warehouses, like Amazon Web Services, Microsoft Azure, and on-premise databases. Looker’s powerful integration capabilities will help marketers who currently use BigQuery for data warehousing, and it will also help marketers who have more complex cloud warehousing strategies that require the integration of non-Google data warehousing platforms. This is a powerful advantage for marketers who require data storage outside of BigQuery because Looker’s platform agnostic integration acknowledges and supports the complexity of cross-warehouse relationships. Looker will help marketers integrate sophisticated BigQuery benefits like machine learning with existing legacy warehouses for a seamless visual business intelligence solution across all marketing data.

  3. Looker’s LookML language unifies data definition across all sources
    Unify data definitions across all data sources for easier and more accurate analysis

    Looker will transform how marketers define business metrics and dimensions across multiple data sources. Looker’s LookML simple modeling language will help marketers build clear, consistent metrics and dimensions across the data sources they already have and will help marketers retain this consistency as their number of data sources grows. This unifying language will give marketers an easy way to search, explore, and visualize their data while maintaining single data definitions for accuracy and clarity. Looker’s sophisticated ability to unify data definitions across multiple data sources provides an easy tool for building a single source of marketing truth and will give marketers maximum insight into both actualized and predicted marketing performance at scale.

  4. Looker’s embedded analytics means easy insight portability
    Make better sense of data sets for highly visual, interactive, embedded analytics

    Looker offers sophisticated embedded analytics, which gives marketers modern developer workflows, scalable and predictable performance, deeply customizable reporting, and a user experience that lets marketing teams drill down and explore their data in a self-serve way. Looker’s embedded analytics will help Google Cloud Platform customers expand the accessibility of valuable, interactive insights, and allow Google Cloud Platform customers to insert this data accessibility into multiple business applications quickly and easily. Looker’s embedded analytics capabilities will integrate seamlessly with Google Cloud Platform products, giving marketers a powerful and user-friendly tool set to more efficiently unlock deep marketing insight hidden otherwise by the volume and complexity of their marketing data.

  5. Looker brings application-first analytics to Google Cloud Platform
    Reduce time to launch for more efficient marketing programs

    Looker is a powerful, application-first business intelligence tool that will integrate seamlessly with Google Cloud Platform’s application agnostic products. This means that Looker’s powerful data science capabilities will offer Google Cloud Platform customers the additional building blocks required to build sophisticated, customized, full stack marketing solutions without the complex time dedication typically required for custom builds. Looker includes a multitude of pre-built application integrations, which solves real world marketing problems by helping analysts and developers focus more on results and worry less about the complexity of custom integration development and associated challenges with data accuracy.