Key Outcomes

76%

improvement in overall data processing time

Near real-time

master data availability for downstream consumers

80%

reduction in CPU utilization through query optimization

90%

reduction in outbound processing time through parallelization

Enhanced

data quality and reliability across enterprise systems

Executive Summary

A leading premium apparel company partnered with Altimetrik to modernize its enterprise master data ecosystem and improve operational efficiency across merchandising and planning operations. The organization needed a scalable, reliable framework to manage product, vendor, and location data while reducing delays in downstream data availability.

Altimetrik implemented a modernized data engineering architecture with advanced validation, parallel processing, near real-time data streaming, and enhanced telemetry. The transformation significantly accelerated data delivery, improved data quality, optimized infrastructure efficiency, and enhanced the overall retail customer experience.

Client Snapshot

Industry
Retail & Consumer Packaged Goods (CPG)
Client Profile
A leading U.S. premium apparel retailer managing enterprise-scale product, vendor, and location master data.
Business Focus
Modernizing retail master data management and data engineering to enable near real-time data availability, improve operational efficiency, and enhance customer experiences.

The Challenge: Slow Master Data Undermines the Retail Customer Experience

Frequent rule changes and evolving business attributes let flawed data slip through the existing architecture, creating downstream issues for end users. Onboarding new data took roughly 25 hours, and routine updates required 3 hours, largely because a single monolithic pipeline generated massive files, sometimes running into gigabytes.

Debugging was slow and labor-intensive, and sequential processing pushed server memory and CPU usage as high as 90%, further delaying publication. The team was not short on effort; the architecture simply could not keep pace with the business.

Why It Mattered

Accurate, timely master data is essential for delivering seamless retail experiences and efficient operations. By replacing a slow, monolithic pipeline with a scalable, near real-time data engineering platform, the retailer improved data quality, accelerated decision-making, and established a modern foundation for future enterprise growth.

The Solution: A Modern, Real-Time Retail Data Engineering Pipeline

Altimetrik partnered with the client to re-architect the master data pipeline end to end, moving it from a slow, monolithic process to a fast, transparent, near real-time system. The solution delivered five core capabilities:

  • Validation Layer: Added an additional data validation step just before the enterprise data exchange to catch flawed data and instantly notify the support team for fast resolution.
  • Parallel Processing: Broke the monolithic file into smaller files that could be processed in parallel, cutting outbound file processing time from roughly 10 hours to about 1 hour.
  • Real-Time Data Availability: Replaced batch-generated JSON files with direct queries from the MDM system streamed into Kafka every hour, removing file creation and retrieval delays entirely.
  • Enhanced Data Tracking: Introduced a correlation ID framework to trace every data batch from inbound to outbound, including third-party systems, for full pipeline visibility.
  • Optimized Queries: Refined query logic to run a single consolidated query across all IDs instead of many smaller ones, sharply reducing CPU load.

Business Outcomes

76% Faster Data Processing

Accelerated enterprise data pipelines, enabling quicker access to critical business information.

Near Real-Time Data Availability

Delivered continuously updated master data to downstream applications with minimal latency.

Improved Infrastructure Efficiency

Optimized processing and query performance, significantly reducing CPU utilization and system overhead.

Higher Data Quality

Strengthened validation and monitoring to improve the accuracy and reliability of enterprise data.

Scalable Data Foundation

Built a modern data engineering architecture capable of supporting future growth, new channels, and evolving business needs.

Altimetrik Advantage

This engagement reflects how Altimetrik approaches data engineering: not as a one-time fix, but as the foundation for what a business builds next. By replacing a rigid, monolithic pipeline with a fast, transparent, scalable architecture, Altimetrik gave the client’s team the speed and confidence to support downstream systems and customers with accurate, near real-time information.

The work continues. The client and Altimetrik are extending this foundation toward a fully scalable, enterprise-wide data-as-a-service model, one built to flex as new business needs, channels, and data sources emerge.

Amit singh

“Amit Singh is the Chief Strategy Officer and Chief of Staff to the CEO at Altimetrik, where he drives corporate strategy, growth acceleration, and value creation through transformation initiatives. In this dual role, he partners closely with leadership teams, investors, and the board to align business strategy with sustained, technology-driven growth.

With over two decades of experience at the intersection of technology, business, and transformation, Amit brings a unique perspective on how organizations can innovate and adapt in a rapidly evolving digital landscape. His career has been defined by building high-performing teams, scaling innovative platforms, and driving organizational change to deliver lasting impact.

Before joining Altimetrik, Amit held senior leadership roles at Visa, where he led technology strategy, engineering, and product development for Real-Time Payments and the Visa Developer Platform. Earlier, he served as Chief Product Officer at a startup and spent more than a decade at Oracle, leading product and engineering teams across a wide range of enterprise software applications.”

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