A U.S.-based manufacturer of building products struggled to extract and transform data in a meaningful way. Bringing in new data sources was difficult and manual.

Working with NTT DATA, the manufacturer revamped its data strategy and introduced a multi-source technology platform. Doing so moved the client from a chaotic data landscape to a set of targeted analytics products that make it easy to quickly and accurately analyze the data that drives its business — today and in the future.

Business Needs

Toward the tail end of a multi-year, enterprise-wide SAP implementation, a building products manufacturer faced several challenges in accomplishing its analytic objectives. IT teams struggled to enrich, extract or transform data in any meaningful way amid multiple data sources and custom hierarchies. Key ERP and transportation management modules in SAP couldn’t easily talk to each other. And when teams tried to bring in third-party data to increase visibility in specific areas of the business (like shipping logistics), the process required even more time and manual effort.

Providing management with useful reports was arduous — and understanding trends across historical data sets was nearly impossible. Without a single of source of truth, key areas of the business — sales, finances, logistics and manufacturing — lacked the insights needed to make strategic decisions.


$3-$5M annual savings with freight lane optimization
6K hours saved through cloud use
  • Adopts a scalable platform to get needle-moving insights
  • Improves reporting and business visibility


The company understood that getting on the right analytics path would require more than just technology and worked with NTT DATA to design and build a modern data and analytics strategy, one that would provide the manufacturer with a better, more scalable data foundation for developing the analytics products it needs today and in the future.

Together, the teams succeeded in:

  • Defining an analytics product roadmap that identified a list of analytical use cases and prioritized them based on value and alignment to vision and establishing KPIs for each phase of development.
  • Creating an end-to-end scalable analytical platform based on Snowflake and utilizing multi-cloud resources to enable the roadmap.
  • Extracting more than 200 tables from the client’s existing SAP system using Azure Data Factory and landing raw exports into Azure Data Lake Gen2.
  • Building a curated multi-dimensional layer using Databricks that loads into Snowflake, combining multiple input sources and applying business logic, custom hierarchies and record-level attributes.
  • Identifying and integrating third-party data sets from Snowflake that enrich existing data and decision making.

With a coherent strategy in place and the data easily accessible, the teams created 12 certified data models and 20 certified Power BI dashboard products, and then trained 150-plus users on how to create and consume reports.

By replacing the client’s time-consuming manual data collection and analysis process with an auto-feed of freight lane rates from the Snowflake Data Marketplace, the team identified an estimated $3-$5 million in annual savings.

Accurate and timely dashboards are now just a click away for business users across departments and hierarchies. Business teams can pull indicator reports on a regular basis and adjust their pricing, sales, customer service or manufacturing strategies to maximize opportunities.

The company now understands and manages the use and associated costs of their new cloud-based data and analytics environment. The resulting savings — including an estimated savings of 6,000 hours — and the shifting of the funds they enabled helped offset the cost of the overall investment.

About the case study

A building products manufacturer defines an analytics product roadmap and creates a scalable analytical platform to improve reporting, business visibility and cost optimization.




United States

More Case Studies