Amazon advances QuickSight with new embedded analytics tool
Coming after the addition of natural language processing capabilities, the new embedded analytics tool strengthens the BI platform to make it more feature rich.
Amazon has added new embedded analytics capabilities to QuickSight, the tech giant's business intelligence platform.
Amazon first introduced QuickSight in 2016, and initially the perception of the BI platform was that it was a solid but somewhat basic option differentiated most by its inexpensive price.
In late 2021, however, Amazon unveiled QuickSight Q, a tool that enables users to work with data using natural language rather than code. And though other analytics vendors, including Tableau, ThoughtSpot and Yellowfin, have natural language processing (NLP) capabilities, QuickSight Q was regarded as a tool that might help accomplish the crucial goal of enabling more users within organizations to work with data.
According to several studies, it's estimated that only about a quarter to a third of employees in most organizations use data and analytics as part of their decision-making. That percentage has remained steady for many years.
Now, Amazon's introduction of new embedded analytics capabilities for QuickSight on Aug. 25 could help more QuickSight users work with data.
New embedded capabilities
With the introduction of fine-grained visual embedding, organizations developing applications for their own analytics use and independent software vendors (ISVs) building applications for third parties with Amazon tools can now quickly and easily embed individual visualizations from QuickSight into apps and web pages, according to Amazon.
As a result, developers can provide relevant insights to end users within their everyday workflows.
And given that fine-grained visual embedding lets developers embed not merely whole dashboards but also individual elements that make up dashboards and are most relevant to potential users, it has the potential to be a significant tool for QuickSight users, according to David Menninger, analyst at Ventana Research.
"I am a big proponent of embedded analytics," he said. "Fine-grained embedding is critical to effectively integrate analytics into other applications. Merely grabbing an entire page and putting it someplace else is better than nothing, but it's not really integrated. Ideally you want fine-grained components and API access to manipulate those components as necessary."
Application developers can use fine-grained visual embedding to embed individual elements from dashboards in two ways, according to Amazon.
They can use one-click embedding, a pre-existing QuickSight capability that lets users with registered access to a dashboard get the embed code by choosing the visual element they want, then selecting menu options and simply clicking on embed visual.
With an API, developers and ISVs can use AWS' command line interface or software development kit to embed the element alongside data governance measures, such as access controls and row-level security.
"QuickSight started as a basic product, but Amazon has continued to invest to make it more capable and relevant to more of the market," Menninger said. "For those organizations that are committed to an AWS stack it is a reasonable alternative, especially if they plan to use the new embedding capabilities."
Strengths and weaknesses
Despite Amazon's commitment to improving QuickSight's capabilities, the platform still lacks some functionality, according to Menninger.
He noted that many end users struggle to interpret dashboards, and useful means of helping users glean insight from their dashboards include collaboration with colleagues and automated insight generation. Vendors such as Qlik and ThoughtSpot have added tools that enable collaboration, while MicroStrategy and Tableau aid data interpretation using NLP.
"Most analytics products do a good job with interactive dashboards, [and] this still one of the most commonly used type of analytics," Menninger said. "But even though they are commonly used, not everyone knows how to use a dashboard, so better guided analytics and collaboration around the analytics processes would make QuickSight more valuable to its customers."
David MenningerAnalyst, Ventana Research
Where QuickSight excels, however, is in its integration with the rest of the AWS portfolio, according to Menninger.
For example, for organizations that store their data in Amazon Redshift or use Amazon SageMaker for their development of machine learning models, QuickSight is a strong option given the way it was developed to interact with the rest of the AWS ecosystem.
In addition, like analytics vendor Domo, Menninger noted that QuickSight is one of the few BI platforms that was cloud-native from its inception rather than retrofitted to work in the cloud as most other BI platforms were.
"QuickSight has two main strengths overall: it's a cloud-native analytics platform, and it's tightly integrated into the AWS portfolio of cloud services," he said.