Vyaire Uses AWS Data Exchange to Keep the World Breathing Better
Global medical company Vyaire had grown through multiple mergers and acquisitions over its 65-year history. As a result, the company’s 4,000 employees were using more than 13 ERP and CRM systems, which combined with increasing use of advanced analytics and machine learning, created a large and complex data ecosystem. To be able to make better, data-based decisions utilizing both first-and-third-party data, Vyaire runs its analytics on Amazon Web Services (AWS) and utilizes AWS Data Exchange to find, subscribe to, and use third-party data.
Going to the AWS Data Exchange catalog made me feel like a kid in a candy store. There is a huge variety of data available to just grab and go; you can build, and experiment, and just start using what makes sense for your business.”
Vice President for Analytics and Global Data Management, Vyaire Medical
Vyaire Medical had reached a point where managing data was getting in the way of doing business. The only global company focused exclusively on respiratory care products, Vyaire has been expanding on its expertise for over 65 years, in part by merging with other industry innovators. That has led to the development of a robust product line, but a complicated technical ecosystem.
The company offers more than 27,000 unique products to more than 350,000 customers in 127 countries. Managing the data that the business generated was extremely complex; the company’s 4,000 employees were using more than 13 enterprise resource planning (ERP) and multiple customer relationship management (CRM) systems.
Gopal Ramamurthi, vice president for analytics and global data management at Vyaire, needed to simplify and streamline this complex environment so that the company can utilize advances in analytics and machine learning for growth. “We knew that not making data work for us and provide us with insights meant that we were missing opportunities—to better serve our customers and innovate on their behalf,” says Ramamurthi. “That’s why we found the market leader and built an entire analytics suite on AWS.
Data-Based Innovation and Growth
The demand for Vyaire’s products—neonatal ventilators, airway management devices, respiratory management items, and operative care technologies—tends to fluctuate. For example, during flu season, demand for airway management solutions increases in regions facing their winter months. During the COVID-19 pandemic, Vyaire had to balance demand for ventilators from hospitals all around the world.
Ramamurthi knew that the most efficient way for the company to ensure that it has sufficient stock and that supplies are sent to where they need to be is to use both historic and predictive data. More data made for better analytics which made for better decisions.
“As we matured in our analytics journey, we got to a point where we wanted to expand into artificial intelligence and machine learning to fuel growth and increase our market presence,” he says. “And for that, we needed more than just our own, company-generated data.”
Finding, licensing, and ingesting the external data that Vyaire needed for better analytics and to power artificial intelligence (AI) and machine learning (ML) was a challenge—searching multiple sources to find the right data, dealing with time-consuming licensing processes, and getting the data ready for analysis—was all undifferentiated heavy lifting that took up engineering resources. The solution to that problem, says Ramamurthi, was AWS Data Exchange, which makes it easy to find, subscribe to, and use third-party data in the cloud.
AWS Data Exchange for APIs Simplifies Access to Third-Party Data
Vyaire saw both the business and technical benefits that came from adopting AWS Data Exchange for APIs as soon as the product was launched in November 2021. For the business, using APIs has made it easier to find data and faster to incorporate data sources into the company’s own environment, resulting in quicker insights and teams that focus on getting results, not administration.
On the technical side, using AWS Data Exchange for APIs has standardized the authentication process by enabling developers and data scientists to use their AWS credentials, and streamlined the process of calling third-party APIs through the AWS Software Development Kit (SDK).
The security of AWS ensured that Vyaire could keep sensitive customer data safe and in compliance with regulations such as HIPAA and GDPR, and leverage tools such as AWS Identity and Management.
Easy access to third-party data gave the company the freedom to innovate. “Going to the AWS Data Exchange catalog made me feel like a kid in a candy store. There is a huge variety of data available to just grab and go; you can build, and experiment, and just start using what makes sense for your business.”
Third-Party Data Delivers Deeper Insights
Vyaire is in a better place than it was, says Ramamurthi, thanks to better analytics and data-driven decision making. And he expects those benefits to grow. “AWS is always inventing so I really don't have to spend time looking for a newer solution,” he says. “I go to my account rep and there is usually a solution that I can bank on.”
Vyaire is a global company focused exclusively on respiratory care. The US-based company has grown by acquisition and merger of brands over a 65-year history. The company offers more than 27,000 unique products to more than 350,000 customers in 127 countries, all served by more than 4,000 employees.
Benefits of AWS
- Faster insights from data
- Easier data-driven decision-making
- Reduced administrative overhead
- Consolidation of multiple data silos
AWS Services Used
AWS Data Exchange
AWS Data Exchange makes it easy to find, subscribe to, and use third-party data in the cloud.
Amazon QuickSight allows everyone in your organization to understand your data by asking questions in natural language, exploring through interactive dashboards, or automatically looking for patterns and outliers powered by machine learning.
Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning to deliver the best price performance at any scale.
Amazon SageMaker is built on Amazon’s two decades of experience developing real-world machine learning applications, including product recommendations, personalization, intelligent shopping, robotics, and voice-assisted devices.
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