MJN powers data breakthrough with Tiger Analytics and Microsoft Azure

Tiger Analytics helped pediatric nutrition giant Mead Johnson Nutrition modernize their data pipeline to support scalable insights, faster decisions, and AI readiness.

November 3, 2025

In the race to innovate, global enterprises aren’t usually held back by a lack of ideas but rather by the friction hidden in their data. Legacy SAP systems, siloed data storage environments, and inconsistent data structures can quietly slow operations, including reporting, forecasting, compliance, and even cutting-edge AI adoption.

This friction can be especially acute in the retail life sciences and consumer health sectors, where any new products must adhere to strict standards of safety and scientific rigor, all at an enterprise scale. In these data-intensive environments, the stakes are high, and the pressure to innovate safely and without business disruption is even higher.

Healthcare and consumer health organizations need a partner who can help them move fast while respecting the boundaries, systems, and regulations that keep them compliant. In other words, they need a partner with the speed and precision of a tiger—and Tiger Analytics is true to their namesake.

Founded in 2011, Tiger Analytics is an innovator in AI and data science consulting with a team of more than 6,200. A Microsoft partner with specializations in Analytics and AI and Machine Learning, the team helps enterprises around the world modernize complex data ecosystems at scale so they can harness insights for real-world innovation. With deep experience in SAP, data engineering, and Azure cloud services, they’ve built a reputation for solving high-stakes data challenges with clarity and speed.

And it was these capabilities that made Tiger Analytics an ideal option when global pediatric nutrition leader Mead Johnson Nutrition (MJN) decided to transform their digital operations and lay the foundation for faster, more efficient, and scalable enterprise AI.

Modernizing data architecture to fuel smarter innovation

With more than a century of experience developing science-based formulas for infants and children, MJN serves millions of families in highly regulated markets across North America, Asia, and Latin America.

The scale of their operation makes any digital transformation a significant undertaking. So when they initiated a major effort to modernize their enterprise resource planning—which included migrating from SAP ECC to SAP S/4HANA—there was some inherent risk involved. The switch disrupted the existing data replication layer that fed analytics and reporting systems across the enterprise.

To maintain business continuity, MJN needed to rapidly rebuild and enhance this layer. MJN already had an established partnership with Tiger Analytics, having worked with them on various data engineering initiatives. MJN brought Tiger Analytics in again to help design, build, and operationalize the new replication layer, enabling seamless data flow from the upgraded S/4HANA system to MJN’s analytics platform. MJN outlined three key strategic goals they needed the solution to support:

Real-time replication from S/4HANA into the DnA Delta Lakehouse for advanced analytics, AI and machine learning use cases, and enterprise-wide reporting.
Clean and secure nutrition data delivery from SAP S/4 to the Global EDAP team, which manages centralized analytics and data processing across business units.
A smooth, timely transition to ensure business teams retained access to business-critical SAP tables.

With MJN's goals clearly articulated and the partnership already well established, Tiger Analytics was ready to get to work.

"We can now operationalize insights across functions... SunRise2 is unlocking new levels of agility and intelligence in how we run the business.”

—Ganesh Sivakumar, Global CDA & AI Officer, Mead Johnson Nutrition

Engineering a comprehensive solution for MJN’s data

Tiger Analytics set out to design a scalable, metadata-driven, and auditable data pipeline architecture built to meet MJN’s immediate needs and pave the way for future innovation. But they needed to do it within certain key constraints, including working within architectural constraints; preserving, replicating, testing, and deploying more than 140 high-priority tables; and coordinating with multiple downstream systems and teams, many of which had tight dependencies on legacy SQL Server pipelines.

And they had to navigate it all and deliver the solution on a tight timeline of just eight weeks.

“With years of experience working with MJN on data engineering initiatives, we were able to quickly understand the landscape, align with technical and business stakeholders, and move from planning to execution in record time,” said Asif Ghatala, VP and Business Unit Head at Tiger Analytics.

The team designed and delivered a robust modernization blueprint that brought MJN’s legacy SAP environment into a secure, cloud-native architecture without disrupting ongoing operations. They came up with an internal codename for the project to represent the dawn of MJN’s new era: SunRise². The solution involved multiple deployments, including:

Graphic featuring the multiple deployments in the solution.

“With a harmonized SAP data foundation, we can now operationalize insights across functions, from supply chain and finance to marketing and product innovation,” said Ganesh Sivakumar, Global CDA & AI Officer at MJN. “SunRise² is unlocking new levels of agility and intelligence in how we run the business.”

A person giving a bottle to a baby supervised by a nurse.

“With years of experience working with MJN on data engineering initiatives, we were able to quickly understand the landscape, align with technical and business stakeholders, and move from planning to execution in record time.”

—Asif Ghatala, VP and Business Unit Head at Tiger Analytics

Feeding innovation now and into the future

Already, MJN employees are seeing faster, more reliable reporting performance and reduced dependence on legacy SQL Server pipelines. With more than 140 tables deployed spanning development, UAT, and production, Tiger’s metadata-driven architecture is delivering near real-time data at 30-minute intervals, aligned to the cadence of downstream teams.

Now, with those initial issues addressed, Tiger Analytics is helping MJN work on the next phase of their modernization.

"Our work didn’t stop at go-live,” said Ghatala. “After stabilizing the replication pipeline, the team made strategic enhancements to future-proof the architecture."

To reduce dependencies and support long-term flexibility, the team also introduced a system of Databricks history tables, an enhancement that’s already driving improved performance and accelerating reporting.

By remaining a key partner on MJN’s digital transformation journey, Tiger Analytics is helping them make smart, transformational improvements, while allowing the teams at MJN to stay focused on their broad goal of using data to deliver better outcomes for children and families around the world.

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