AWS Business Intelligence Blog

Prevsis safety and sustainability software solutions help customers make informed decisions with Amazon QuickSight

This is a guest post by Alex Cabrera, Harvey Rosas and Camilo Gómez from Prevsis.

In this post, we share how Prevsis used Amazon QuickSight to create more than 700 client dashboards. Prevsis aims at caring for workers’ safety, well-being, and corporate sustainability. It focuses on delivering a no-code occupational health and safety (HS) and environmental, social, and governance (ESG) solution with a wide range of data pipelines for robust analytics harvesting with AI capabilities. Users in high-risk industries such as mining, energy, construction, and logistics can digitally manage all their safety and compliance needs through a one-stop interface.

As one of the leading digital service providers in the HS/ESG field Latin America, we capitalize on decades of experience to help customers assess and monitor risk levels, enhance operational efficiency, and minimize disruptions across the workplace.

Providing a single, evolving solution for HS and ESG

Our clients need insight analytics to fuel their decision-making process and positively impact their HS and sustainability goals. We sought an efficient, powerful, and flexible business intelligence (BI) tool that could combine mountains of data and turn it into real, actionable insights through the power of AI analytics—not just to help our customers understand what’s happening in their organization, but to help them make informed decisions and act proactively to prevent issues.

Our BI solution needed to allow us to present data to customers in a visually compelling manner to different stakeholders with different needs—without extensive work customizing or embedding it. We also wanted to make it as easy as possible for any user to get what they needed, so any features that could assist with that—such as drag-and-drop dashboard editors and other user-friendly tools like natural language querying—are a big plus.

Finally, HS is about preventing mistakes. We knew predictive analytics and AI would help us bring added value to our customers, because they would be able to analyze their own historical data and identify patterns or trends that could lead to safety or health risks in the future and track their progress and improvement over time.

However, for all these features to be available to customers in a timely manner, we needed to take new features from development to the production environment swiftly while minimizing cost and effort and maintaining scalability.

QuickSight: Providing greater value to users while reducing costs

After careful evaluation of various BI alternatives, we chose QuickSight for the following reasons:

  • Reduced cost – QuickSight provided significant savings, with a 45% lower cost of implementation compared to other BI alternatives. Usage-based pricing increased our savings and allowed us to offer access to external users through anonymous embedding (because we don’t have to pay per user). This reduced our overall expenses while delivering exceptional value to our customers.
  • Fully managed, auto scaling infrastructure – QuickSight allowed us to scale our usage freely without requiring us to manage and maintain any complex infrastructure. This frees up our resources and lets us focus on our core competencies and innovation.
  • Governed data access – The advanced data segmentation capabilities of QuickSight, including row-level security (RLS), allowed us to restrict access to specific datasets based on user roles and permissions. This provides data privacy and compliance while empowering our clients with tailored data access.
  • Easy reporting and customization – The built-in customizable and embeddable dashboards in QuickSight make it straightforward for us to bring the decision-making power of data analytics to our customers, and make it effortless for end-users to generate useful reports from a centralized pool of data. The fact that users can go from the dashboard, pull a report, and head straight into a presentation meeting to deliver their findings is uniquely powerful.
  • Productizing BI with SDKs – The QuickSight software development kit (SDK) capabilities play a vital role in revolutionizing our deployment process. With the SDK, we were able to deploy our data products into production quickly and effortlessly, significantly reducing manual effort.

We also have a largely AWS-centric tech stack, with Amazon solutions embedded from extraction to production, so using QuickSight for our BI needs seemed like a natural next step.

Sleek embedded analytics, delivered with QuickSight

QuickSight has made it straightforward for us to bring value to our customers and users. Our analytics products now revolve around embedded analytics, with a particular focus on QuickSight dashboards.

As part of our service, we integrate dashboards into every service to enhance functionality and deliver valuable insights to users. QuickSight’s intuitive dashboard creator allows us to create beautiful, modern dashboards to serve relevant data insights to our customers.

At this point, we provide more than 700 embedded dashboards within our solution, which are served to our customers, each with the capacity to serve any user, employee, or thousands of contractors. These dashboards allow customers to assess the performance of a variety of HS and ESG requirements, including incident and accident reporting, training, safety program adherence and violations, and leading and lagging indicators, to name a few.

The following video shows our Incidents Analytics dashboard in action.

The following illustrates our ability to visualize frequency, severity, and total injury index rates, with a pivot table for divisions.

Dashboard to visualize frequency, severity, and total injury index rates, with a pivot table for divisions.

The following illustrates an example safety pyramid.

Example of safety pyramid.

The following dashboard visualizes acts and conditions with origin, type, and criticality.

Dashboard to visualize acts and conditions with origin, type, and criticality

Our data stack

At Prevsis, our data stack relies heavily on the AWS ecosystem. We chose a serverless architecture, given its performance, low cost, and low maintenance. Some of the tools we use are:

These tools, in conjunction with QuickSight, made it possible for us to offer a robust and comprehensive data analytics ecosystem that empowers our clients with valuable insights and streamlined compliance processes. The following diagram illustrates the solution architecture.

Solution Architecture

A personalized and consistently high-performing user experience

The results post-deployment have been incredibly promising. We’ve found QuickSight speeds up the process across the entire value chain—from our own internal processes to our customers’ access to and use of data. Every user we’ve spoken to, both internal and external, has loved how reliable the solution is compared to other, clunkier BI tools. Our customers have especially loved the built-in analytics capabilities and dashboards—we’ve been told that the customized dashboards make the user experience feel very personalized and sleek. The instant reporting capabilities also make it straightforward for them to make educated decisions based on data, both historical and current, and to go into meetings and presentations equipped with all the relevant data insights they need.

We’ve found QuickSight incredibly useful internally too. It’s not just about costs; we’ve also experienced a significant reduction in our time investment in everything, including maintenance and operational requirements, development time, and time to deployment. For development specifically, we’ve seen a 50% decrease in time investment, which has freed the team up for more advanced feature development. It’s also incredibly freeing to know that, even with minimal effort on our part, we can provide a top-of-class user experience for our customers and colleagues.

The consistent (and speedy) release of new functionalities is another fantastic thing about QuickSight. Over the time we’ve been using it, we’ve seen visual enhancements to the QuickSight console along with new capabilities within the SDK. All in all, we’re very pleased with our choice to use QuickSight and are looking forward to the latest upcoming features, especially in the areas of new visualizations and data management capabilities.

Going forward

Over the coming year, our roadmap for analytics and BI in Prevsis is set to undergo significant enhancements, and QuickSight is a key part of our strategy. We’re gearing up to integrate continuous integration and continuous deployment (CI/CD) processes in managing dashboards at scale, ensuring seamless updates and improved agility. Additionally, our focus on granting the flexibility for our customers to create and edit their own dashboards, as well as our focus on data observability, will provide unparalleled insights into data quality and performance. Furthermore, we’re excited to introduce the ability to author embedded experiences, empowering users to craft personalized and immersive interactions within our solution. These developments mark an ambitious step forward in our commitment to delivering a more robust and user-centric analytics experience.

Watch this enlightening webinar where Prevsis dives into the future of intelligent HS and ESG data management:

Get started with QuickSight

Migrating to QuickSight enabled Prevsis to streamline its data deployment processes, enabling us to deliver cutting-edge, accessible analytics solutions straight to customers.

With QuickSight as a key component of our data stack, we have established ourselves as a trusted partner for informed decision-making, solving current and future market needs in the ever-evolving landscape of HS and ESG compliance.

To learn more about how QuickSight can help your business with dashboards, reporting, and more, visit Amazon QuickSight.

About the Authors

Alex Cabrera is the CEO of Prevsis. His leadership is driven by the company’s mission: to be the primary partner for customers in making informed decisions through innovative solutions that address current and future market needs. His focus extends beyond technological advancement to encompass the well-being of the workforce and the long-term sustainability of the organization. His overarching mission is to empower clients with an end-to-end solution, ensuring efficient utilization of data to drive innovation and sustainable growth.

As CTO of Prevsis, Harvey Rosas champions the technological trajectory with a specialized focus on AI and advanced analytics. Harvey’s strategic vision revolves around leveraging AI and advanced analytics to empower businesses with transformative insights, enhancing decision-making processes, and fostering innovation. His mission is to fortify the company’s position as a leader in AI-powered solutions, amplifying its capabilities to meet the evolving needs of clients in an ever-changing landscape.

Camilo Gómez is a Lead Data Engineer at Prevsis. On a daily basis, he and his teams are passionately focused on design and implement practical and scalable cloud solutions to solve business or operations opportunities related to data management and decoupling services in the context of Prevsis software ecosystems.