David Menninger's Analyst Perspectives

Google is a Vendor of Merit in 2021 Value Index for Analytics and Data

Posted by David Menninger on Jul 13, 2021 3:00:00 AM

We are happy to share some insights about Google Looker drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

VR_VI_Analytics_and_Data_Logo (4)-2We published the Ventana Research Value Index: Analytics and Data 2021, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on analytics and business intelligence focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern BI, we developed specific criteria to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

In all of our Value Indexes, we utilize a structured research methodology that includes evaluation categories designed to reflect real-world criteria incorporated in a request for proposal and vendor selection process for analytics and business intelligence. We evaluated Google Looker and 17 other vendors in seven categories: five relevant to the product – Adaptability, Capability, Manageability, Reliability and Usability – and two related to the vendor – Total Cost of Ownership/Return on Investment and Vendor Validation. To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and on data derived from our Benchmark Research on Analytics and Business Intelligence. Google’s overall performance rating is 53.9% in the Value Index, with a customer experience rating of 55.2% and a product experience rating of 53.7%.

Ventana_Research_Value_Index_Analytics_and_Data_2021_Vendor_Overall_Chart_Google@2xGoogle entered the BI market in 2020 as it completed its acquisition of eight-year-old Looker. It was categorized as a Vendor with Merit and ranked 17th overall in this Value Index evaluation. Google Looker performed its best in the Manageability and Validation categories.

Looker runs in the cloud or on-premises. Data resides in source databases and is accessed as necessary for analyses. The product provides a highly customizable environment using LookML, Looker’s modeling language, to enable personalized experiences. It also has good administrative capabilities for both IT and business.

Better support for a variety of roles without requiring customization via LookML would improve Looker’s Usability rating. More collaboration and information delivery capabilities would improve its Capability rating, as would a wider variety of analytics including predictive and planning capabilities.

Collaboration among a team of individuals is an effective way for an organization to interpret the results of analyses, choose a course of action and track the implementation of those actions. Most of today’s analytics and business intelligence products support some form of collaboration. Looker’s collaboration abilities primarily consist of emailing and sharing reports and visualizations. Looker also supports alerting and notifications based on thresholds, which can be used to inform collaborators of changes requiring their attention. And, of course, Looker visualizations can be used to support collaboration and dialog around critical metrics in an organization. Annotations on analytics objects, support for workflows, tracking tasks to completion and establishing a community for threaded discussions would help improve Looker’s Capability ranking.

Analytics embedded within applications improves access by line-of-business personnel and reduces the effort to collect and assemble data. Nearly three-quarters of participants in our Data and Analytics in the Cloud Benchmark Research said they considered embedded analytics important. Looker provides REST application programming interfaces along with software development kits for Ruby, Python and JavaScript. Custom themes are supported to change the appearance of embedded visualizations. Additional visualizations, more query and analytic functionality and natural language processing would improve Looker’s Capability score.

Line-of-business workers expect analytics software to support their mobile work style. Many of these workers switch between desktop/laptop devices when in the office to mobile devices when outside the office, making effective integration between these two modes important. Looker relied on responsive HTML5 for the mobile capabilities we evaluated. This approach works well for tablets and makes it easy to share a single set of content across all devices. Better support for native capabilities of the device would improve Google’s Usability score.

This assessment was based on Google Looker’s analytics products available in December of 2020. Since then, Google has issued multiple new releases, including the general availability of a native mobile application for iOS and Android devices with support for 22 different languages. Other enhancements include filtering across multiple displays on a dashboard, and additional visualizations in the Looker Marketplace. Data sources have been extended to include Databricks and Firebolt. Developers have access to a metadata sidebar to better understand what data is available and how it is being used. More information on the new features in Looker is available here.

Organizations should evaluate data and analytics requirements including collaborative, embedded and mobile capabilities to ensure existing approaches are meeting the organization’s needs. If existing platforms are not satisfying those requirements, organizations should consider whether Google Looker can help meet those needs.

This research-based index is the most comprehensive assessment of the value of analytics and BI software in the industry. Technology buyers can learn more about how to use our Value Index by clicking here, and included vendors that wish to learn more can click here. Read the report here.


David Menninger

Topics: embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

David Menninger

Written by David Menninger

David is responsible for the overall research direction of data, information and analytics technologies at Ventana Research covering major areas including Analytics, Big Data, Business Intelligence and Information Management along with the additional specific research categories including Information Applications, IT Performance Management, Location Intelligence, Operational Intelligence and IoT, and Data Science. David is also responsible for examining the role of cloud computing, collaboration and mobile technologies as they affect these areas. David brings to Ventana Research over twenty-five years of experience, through which he has marketed and brought to market some of the leading edge technologies for helping organizations analyze data to support a range of action-taking and decision-making processes. Prior to joining Ventana Research, David was the Head of Business Development & Strategy at Pivotal a division of EMC, VP of Marketing and Product Management at Vertica Systems, VP of Marketing and Product Management at Oracle, Applix, InforSense and IRI Software. David earned his MS in Business from Bentley University and a BS in Economics from University of Pennsylvania.