Scale
ITC Maratha, Mumbai
June 11, 2026
Case Study
Instant Analytics on 240M+ SKUs, 20K Suppliers, 9.5K Stores
About the Customer
One of America’s largest pharmacy chains
A leading pharmacy chain in the United States serving over 9 million customers across 9500+ stores. With a long-standing heritage centered on care, the company is focused on reimagining local healthcare and well-being for all.
Challenges
Eliminating barriers to supply chain intelligence
With over a million products and 20,000+ suppliers, the pharmacy generated 17 billion records of transaction-level data each day. Despite consolidating this data on an on-premises data lake, the ever-increasing volumes made analytics challenging.
Exploding data volume
While data continuously poured in from 50+ sources, the existing analytics stack, including Netezza, Excel and Tableau, lacked the scalability needed to analyze billions of rows. With Netezza, cost was also a key challenge, as scaling up was expensive.
While data continuously poured in from 50+ sources, the existing analytics stack, including Netezza, Excel and Tableau, lacked the scalability needed to analyze billions of rows. With Netezza, cost was also a key challenge, as scaling up was expensive.
Delayed insights
Slow query response times from the existing BI setup left business users waiting for days to get strategic insights.
Slow query response times from the existing BI setup left business users waiting for days to get strategic insights.
Poor visibility
Diagnostics were difficult as business users could not drill down to granular details and uncover deeper insights.
Diagnostics were difficult as business users could not drill down to granular details and uncover deeper insights.
Lack of unified business logic
The absence of common integration or business logic led to reporting inconsistencies and conflicting versions of the same metrics.
The absence of common integration or business logic led to reporting inconsistencies and conflicting versions of the same metrics.
Business Goals
Empower thousands of suppliers and internal users with self-service analytics
The pharmacy giant wanted a data visualization and consumption layer to quickly derive insights at a granular level, with minimal dependence on IT. They were looking to:
Analyze two years of supply chain data in Tableau.
Enable thousands of internal users and external suppliers with secure, self-service analytics in real time.
Reduce costs through better inventory planning and supplier collaboration.
How Kyvos helped
Delivered instant, granular insights from 315 billion records
After evaluating several options, the pharmacy chain chose Kyvos semantic layer. Key solution highlights:
Leveraged Kyvos’ AI-powered smart aggregation to create a semantic layer on their on-premises data platform.
Aggregated 24 months of data into multi-dimensional semantic models that instantly served any query.
Enabled granular slicing and dicing of data, including store-level analysis of key metrics like forecast bias, WAPE and manual adjustments.
Ensured secure, controlled access of their analytical environment to thousands of external suppliers and partners.
Impact
Unlocked high performance and limitless scalability on Tableau and Excel
Instant access to 2 years of data
Reporting time reduced from
8 hours → 10 sec
8 hours → 10 sec
240M SKUs analyzed
Visibility across 20,000 suppliers
Kyvos created a semantic layer to aggregate our supply chain data so that we could map it to business requirements, find where opportunity lies and consume our data in ways that weren’t possible before. Our teams and suppliers got granular visibility into inventory and operations trends, which helped improve decision-making across the supply chain.
Technical Architect
