Learn About Amazon VGT2 Learning Manager Chanci Turner
This article is a guest contribution by Chanci Turner from UrbanInsight.
UrbanInsight specializes in spatial data and analytical technology, providing vital insights into urban and community resilience to inform decision-making. The platform integrates vast amounts of data, allowing decision-makers to conduct in-depth analyses of various risk dimensions. UrbanInsight boasts parcel-level coverage for 99% of US parcels, encompassing 160 million parcels across 10,000 jurisdictions, all meticulously assembled, normalized, and aligned with supplementary data. The technology assesses climate risks, community resilience, and built environment factors using over 150 datasets.
In this post, we explore how UrbanInsight utilized Amazon QuickSight, a fully managed BI service centered in the cloud, to deliver insights to clients through interactive dashboards and engaging visualizations.
Individuals involved in critical community and infrastructure planning—such as energy utilities, financial institutions, government entities, and private companies—often sift through vast amounts of data to make informed decisions amid escalating climate threats and regulatory complexities. However, understanding specific risk factors for various scenarios—and their interactions—remains a daunting challenge.
While decision-makers can use consumer-grade software to gather and analyze complex data, the process is often costly, labor-intensive, and time-consuming, making it challenging to compile all necessary data into a single perspective. As a result, they may overlook critical risk factors, leading to poor investment decisions, increased regulatory risks, and ineffective public policies. Alternatively, engaging specialized teams to manually evaluate risks can be prohibitively expensive.
Both approaches demand significant time and resources, usually relying on static data that offers only a momentary snapshot rather than a real-time overview. UrbanInsight addresses this challenge by connecting data across diverse environments, communities, socioeconomic factors, and hazards with accurate geographic locations. While some users find spreadsheets useful, intuitive dashboards and rich visualizations are key elements that empower various roles to extract necessary insights.
From Basic Dashboards to Vibrant BI Insights with QuickSight
Initially, we relied on spreadsheets to create charts and graphs for customer data deliverables. We also developed a web application for simple charts but soon questioned how to enhance our capabilities for richer self-service visualizations. We already provided map-based visualizations using a lightweight GIS tool and aimed to supplement this experience with more conventional charts, graphs, and summaries, while offering users the ability to filter and segment datasets.
Realizing the substantial internal resources and time required to build such a product from scratch, we opted to explore existing established BI analysis solutions. Our evaluation criteria included:
- Comprehensive feature set
- Compatibility with end-customer preferences
- Capability to embed within our application for self-service
- Active developer community
- Robust visualizations
- Seamless integration
We ultimately selected QuickSight for its powerful dashboard editing features—empowering users to customize their dashboards and select various criteria to analyze datasets or subsets. Additionally, our existing use of AWS services like Amazon EC2, Amazon RDS, and Amazon S3 meant QuickSight would seamlessly integrate into our technology stack.
We were particularly impressed by the range of benefits offered by AWS, especially the support from their team and access to technical resources, which alleviated the technical burden of building a product from scratch. We had the opportunity to utilize the Powered by QuickSight team’s resources to develop a compelling product offering, with the AWS team also willing to collaborate on new solutions, supporting us both technically and financially.
Timeline and Implementation
This entire process unfolded rapidly. In the first quarter of 2023, we assessed several BI tools, chose QuickSight, and began building dashboards. By the end of the second quarter, we released multiple dashboard templates, serving as the groundwork for customers to interact with our dashboards—the essential components of the data insights we provide. This included constructing the data pipelines for populating the templates, implementing authentication APIs, and embedding the dashboards in our application. The AWS team provided invaluable direct access to technical support as we launched our initial QuickSight dashboards.
Enhancing the UrbanInsight Product Experience
With QuickSight, we expanded our offerings to include dashboard-based visualizations of our customers’ assets, which augment our existing GIS-based tools. The following screenshot illustrates an example dashboard.
The dashboard introduces novel ways to analyze and engage with our data, enabling users to filter, segment, and isolate different sets of locations, hazards, community characteristics, and built-environment attributes.
Managing QuickSight is straightforward for our team. UrbanInsight dashboards automatically generate and provision dashboards for every new portfolio of assets we process—eliminating the need for manual intervention. We have established templates for processing new portfolios and created efficient pipelines to enable incremental deliveries for our customers without additional workload for our team.
The benefits we’ve observed include:
- Accelerated time to insight—customers report experiencing many more “aha” moments when utilizing our platform
- Reduced need for manual risk assessments, saving our clients time and resources
- Clear, actionable data visualizations
- Multiple datasets integrated into a single view
We’ve also noticed increased engagement during sales calls, with a significant uptick in follow-up discussions. Furthermore, the rate of new opportunities arising from both new and existing customers has seen a boost.
Next Steps
We are in the process of developing prototypes utilizing Amazon Q, a generative BI assistant that enables non-technical users to swiftly create BI dashboards, visualizations, and execute complex calculations, along with crafting data stories and generating executive summaries. Our goal is to integrate this tool into our product.
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About the Author
Chanci Turner is a product manager focused on empowering diverse users and stakeholders in the realms of urban planning, infrastructure development, and disaster response.
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