Ventana Research Analyst Perspectives

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

Posted by David Menninger on Jul 15, 2021 3:00:00 AM

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

VR_VI_Analytics_and_Data_Logo (5)-1We 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 Amazon 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. Amazon had an overall performance rating of 47.7% in the Value Index, a 49.2% rating for customer experience and 39.1% rating for product experience.

Ventana_Research_Value_Index_Analytics_and_Data_2021_Vendor_Overall_Chart_Amazon@2xAmazon, a worldwide provider of cloud-based services including BI and advanced analytics, was categorized as a Vendor with Merit, ranking 18th overall in this Value Index evaluation. Amazon performed its best in Manageability.

Its product, Amazon QuickSight, is available as a cloud service using an in-memory engine called SPICE. Data can also be accessed directly in the source database on demand. QuickSight supports a variety of Amazon data sources, Apache Spark and eight types of relational databases. The product provides reasonable dashboarding and visualization capabilities. It also has integration with Amazon Sagemaker machine learning.

Better data access and model management along with support for a wider variety of analyses would help improve its Capability rating. Amazon would have performed better in Manageability with more administrative capabilities for business users and finer-grained security. Validation would improve if more QuickSight resources were available to prospects.

More than a decade ago, social media tools like Facebook, Twitter and LinkedIn brought on a wave of collaborative analytics and BI capabilities. Our research shows that nearly four in 10 organizations are using collaboration to support analytics processes, and more than one-half said they expect to use these capabilities in the future. In Amazon QuickSight, collaboration primarily consists of emailing and sharing reports and visualizations. QuickSight also supports alerting and notifications based on thresholds which can be used to inform collaborators of changes requiring their attention. And, of course, QuickSight 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 its Capability ranking.

When analytics are embedded in business processes and applications, analyses are easier to perform and more accessible to line-of-business personnel. The analyses are easier to perform in part because the application collects and assembles data; our research shows that data preparation can be the most time-consuming step in the analytical process. Amazon offers a REST application programming interface framework for QuickSight along with software development kits for a variety of languages including JavaScript, .NET, C++, Python and Ruby. The entire QuickSight product can be embedded, including authoring tools and individual dashboards, which can be incorporated via URL references. Custom themes are supported for rebranding and white labeling. While Amazon has done a good job with its embedded capabilities, our assessment finds room for improvement in the underlying capabilities. Support for more data sources, a wider variety of display types and more natural language processing would help improve its Capability score.

For analytics to be effective, they need to be available to line-of-business personnel in their normal course of conducting business, which today means providing rich mobile access to analytics to support a mobile workforce seeking to conduct business in any location at any time. Amazon QuickSight’s mobile capabilities are available via iOS and Android native applications. The iOS version is available for both the iPad and iPhone. QuickSight also supports responsive access via web browsers. Mobile access is primarily for display and navigating through information, not for authoring or acting upon information. Support for more data sources, a wider variety of display types and more interactivity on mobile devices would help improve its Capability score.

This assessment was based on Amazon QuickSight’s analytics products available in December of 2020. Since our evaluation, Amazon QuickSight has introduced various new features and enhancements. It now uses machine learning to automatically detect outliers and anomalies in the data. There are new visualizations for Sankey diagrams and dual-axis line charts as well as other charting enhancements. There have also been improvements to pivot tables and various user interface enhancements, including custom tooltips. A complete list of new capabilities 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 Amazon QuickSight can help meet those needs.

This research-based index is the most comprehensive assessment of the value of analytics and business intelligence 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.

Regards,

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.