CASE STUDY

Modernizing Data Architecture to Unlock Scalable Insights and Future Innovation

Client: American Association for the Advancement of Science (AAAS)

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scientists and policymakers supported through research and policy initiatives

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employees

At a glance

Challenge

AAAS needed to modernize their data architecture to scale so that they can introduce more datasets quicker and build additional business insights and AI-based solutions using ML and Gen AI.

Result

Pariveda conducted a deep-dive assessment of business needs, data ingestion and transformation tools, data delivery mechanism, to define a target state data architecture to delivery AAAS future demands.

Impact

AAAS has implemented a foundational data platform using the target-state architecture that reduced the time and effort needed to onboard and process new datasets. .

Technologies Used

AWS, Cloud data architecture frameworks, Data ingestion and transformation tools, Analytics and application data delivery platforms

The American Association for the Advancement of Science (AAAS) is one of the world’s largest scientific societies with a mission to advance science for the benefit of all people.

AAAS publishes the prestigious Science journal, advocates for evidence-based policy, promotes STEM education, and supports global engagement in scientific research. As the organization continued expanding its programs, datasets, and digital capabilities, leadership recognized the need to modernize their legacy data architecture to support future growth and innovation.

AAAS partnered with Pariveda to evaluate their existing data ecosystem and design a modern, scalable architecture capable of supporting analytics, application data needs, and emerging AI capabilities.

Modernizing legacy data architecture to support scalable analytics, faster data delivery, and AI innovation.

AAAS relied on a legacy data architecture that limited their ability to efficiently ingest, transform, and deliver data across multiple programs and applications. As the organization continued expanding its datasets and digital initiatives, the existing infrastructure made it difficult to introduce new datasets quickly or leverage advanced analytics and AI-driven insights.

AAAS needed a scalable, future-ready data platform that would allow teams to accelerate data access, streamline transformation workflows, and support multiple downstream use cases including analytics, application APIs, and machine learning models.

Pariveda was engaged to assess AAAS’s current data architecture and develop a strategic modernization plan that would support both current operational needs and long-term innovation.

How Pariveda enabled a modern data platform:

Conducted a comprehensive assessment of AAAS’s data ingestion, modeling, transformation, and delivery pipelines
Leveraged Pariveda’s Modern Data Enterprise (MDE) architectural framework to evaluate the current ecosystem and identify opportunities for improvement
Designed a right-sized target-state architecture on AWS aligned to AAAS’s operational needs and strategic goals
Delivered an actionable roadmap enabling AAAS to incrementally migrate toward a modern, scalable data architecture

AAAS successfully implemented a foundational data platform aligned to the target-state architecture, enabling the organization to onboard and process new datasets significantly faster.

With a scalable architecture in place, AAAS teams can now support a broader set of data use cases—from analytics and application integrations to AI-enabled insights—while reducing operational complexity and reliance on third-party vendors.