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Global Fluid Management Leader Built Unified Data Platform for Prescriptive Analytics

Learn how a global leader in advanced plastic piping systems for building, infrastructure, industrial and agriculture applications partnered with Nihilent to unify data across regions and business units, and to power a new generation of insight-led and prescriptive analytics on Snowflake.

Service

Data & Analytics, Cloud Data Platforms, and Snowflake

Vertical

Manufacturing (Building & Infrastructure Solutions)

Region

Global (Multi‑region operations across EMEA, Americas and Asia Pacific)

Tech Stack

Snowflake, AWS, Azure, SAP S/4HANA, Salesforce (SFDC), Qlik

Global Fluid Management Leader Built Unified Data Platform for Prescriptive Analytics

Client Overview

The client is a Europeheadquartered global leader in advanced plastic piping and fluid management systems, operating through strong local brands in over 40 countries. Their pipe and fitting systems support missioncritical water and energy flows across residential and commercial buildings, public infrastructure, industrial plants and agriculture projects worldwide. 

Over time, rapid growth through regions and brands meant sales, finance and supply chain data was scattered across multiple ERP, CRM and analytics platforms, each with its own structures and standards. Regional teams optimized locally, but the group lacked a single, trusted view of customers, distributors and channel performance across markets. Leadership wanted to move beyond descriptive dashboards into forecasting, prescriptive recommendations and AIready use cases – without disrupting daytoday operations.

Business Challenges

The client needed to modernize its data and analytics foundation but faced several interlinked challenges.

01

Fragmented and Siloed Data Landscape

Core data lived in regional instances of SAP S/4HANA, Salesforce and local BI tools, with no unified Customer Data Management (CDM) layer or common data model across brands and geographies.

02

Inconsistent and Delayed Reporting

Group and regional teams produced their own reports and KPIs, leading to reconciliation overhead, conflicting versions of the truth and slower decision‑making on pricing, promotions and inventory.

03

Limited Support for Advanced Analytics

Data pipelines, governance and compute capacity were not designed to support demanding use cases such as primary sales forecasting, churn prediction and prescriptive recommendation engines at scale.

04

Scaling Across Regions Without Losing Local Nuance

Any solution had to serve both centralized group‑level decision‑making and localized analytics needs for individual business units in sales, finance and supply chain management.

How Nihilent Addressed This

Nihilent designed and implemented a regional data lake architecture on AWS and Azure, anchored by a centralized CDM platform on Snowflake to act as the single source of truth for customer and transaction data. The architecture combined a governed, group‑level data foundation with localized data lakes, allowing regional teams to retain the flexibility they needed while aligning to shared models and definitions.

Unified Data Foundation on Snowflake

Enterprise data from SAP S/4HANA, Salesforce and existing BI systems was ingested, standardized and modeled into a consolidated Snowflake‑based CDM, with conformed dimensions and harmonized KPIs across sales, finance and supply chain domains.

Centralized Reporting with Localized Analytics

A layered architecture separated trusted, centrally governed reporting views from sandboxed, regional analytical zones, enabling group dashboards and localized deep‑dives to run on the same underlying data without conflict.

Industrialized Ingestion and Governance

Automated data pipelines, quality checks and metadata management ensured that data from ERP, CRM and other enterprise systems arrived in Snowflake reliably and at the cadence needed for planning cycles and operational decision‑making.

Advanced Analytics & Prescriptive Use Cases

On the platform, Nihilent enabled a suite of insight and prescriptive analytics use cases - including primary sales forecasting, multi‑dimensional distributor segmentation, and more. This made CDP run across regions while respecting local market context.

Key Results & Outcomes

Single, Trusted View of Customers and Distributors

The centralized CDM on Snowflake now powers group and regional analytics, reducing reconciliation effort and giving leadership a consistent lens on performance across brands and markets.

Insight-Driven Decision-Making at Scale

Unified, near real‑time insights across sales, finance and supply chain domains improved the quality and speed of decisions on pricing, promotions, inventory and channel strategy.

Streamlined Cross-Region Reporting

Centralized reporting backed by a common data model cut duplication of effort, reduced manual report preparation and ensured that regional variations no longer translated into conflicting numbers.

Scalable Foundation for AI and Analytics

The cloud‑native data lake and Snowflake architecture now support a growing portfolio of forecasting, recommendation and optimization use cases without re‑engineering core data pipelines each time.

Future-Ready Architecture

The client is positioned to plug in new data sources, expand to additional regions and introduce more advanced AI and machine learning workloads as business priorities evolve.

Key Takeaways

This transformation was not just a reporting upgrade; it was a structural reset of how data, analytics and decisions flow across a global manufacturing business. By pairing a centralized Snowflake‑based CDM with regional data lakes on AWS and Azure, the client combined global consistency with local agility, turning scattered operational data into a strategic asset that can continuously feed new insight and prescriptive analytics use cases.

On the unified platform, Nihilent enabled a suite of insight and prescriptive analytics use cases, including primary sales forecasting, multi‑dimensional distributor segmentation, distributor and sales‑person performance scorecards, recommendation engines, beat optimization, churn analysis, bill verification, catchment area analysis and image analysis of uploaded bills. These use cases leveraged the cloud data platform to run consistently across regions while respecting local market context.

In an industry where most of the critical work happens out of sight - behind walls, under floors and underground, the right data foundation is what makes high‑stakes decisions feel as seamless and reliable as the flows their systems manage.

Nihilent
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