How a Leading African Food Manufacturer Defined an Enterprise Data Strategy on Microsoft Fabric

Learn how a leading African food manufacturer with a broad portfolio of branded and private-label products partnered with Nihilent to define an enterprise data strategy, rationalize fragmented data warehouses, and design a future-ready Microsoft Fabric Lakehouse architecture for BI and analytics.

Service

Data & Analytics, Enterprise Data Strategy, and Microsoft Fabric

Vertical

CPG (Food and Beverages), Manufacturing

Region

Africa (Operations Across South Africa and Regional Markets)

Tech Stack

Microsoft Fabric, Lakehouse Architecture, Existing Data Warehouses and OLAP Cubes, Reporting Platforms, Dataflows, Governance Frameworks

How a Leading African Food Manufacturer Defined an Enterprise Data Strategy on Microsoft Fabric

Client Overview

The client is one of Africa’s leading food manufacturers, producing a wide range of branded and private-label products across categories such as baking, chicken, grocery, sugar, and pet food. Its products reach consumers across South Africa and neighboring markets through retail, wholesale, and dedicated logistics operations, supported by a complex mix of legacy and modern systems.

As the group grew through acquisitions and business line expansion, multiple data warehouses, OLAP cubes, reporting tools, and dataflows emerged across divisions, each tailored to local needs but difficult to govern centrally. Leadership wanted an enterprise data strategy that would rationalize this landscape, align BI and analytics to future business needs, and provide a clear roadmap toward a modern lakehouse-based platform on Microsoft Fabric.

Business Challenges

The client wanted to become more data driven at enterprise scale but faced several interrelated challenges.

01

Fragmented Data Warehouses and Cubes

Multiple data warehouses and OLAP cubes across divisions increased cost, duplication, and complexity for reporting and analytics.

02

Inconsistent BI And Analytics Foundations

ETL processes, semantic models, and reporting workloads had evolved independently, limiting reuse and making it hard to support new analytics needs.

03

Limited Visibility into Future Requirements

The organization needed a structured view of current and future BI and analytics requirements to guide architecture and investment decisions.

04

No Unified Path to Modern Lakehouse Architecture

While interested in Microsoft Fabric, the client lacked a clear target architecture and transition roadmap to move from legacy platforms to a governed lakehouse model.

How Nihilent Addressed This

Nihilent partnered with the client on a focused six-week engagement to assess the current data and BI landscape, define an enterprise data strategy, and design a Microsoft Fabric-based target architecture with a pragmatic transition roadmap.

Structured Assessment of Data and BI Assets

Nihilent conducted a comprehensive review of existing data warehouses, OLAP cubes, ETL operations, databases used for data warehousing, semantic structures, reporting platforms, and governance practices to establish a clear baseline.

Business-Driven BI And Analytics Requirements

Through workshops and stakeholder interviews, Nihilent assessed current and future BI and analytics needs across functions, ensuring that the strategy and architecture were anchored in real decision-making scenarios.

Target Lakehouse Architecture on Microsoft Fabric

Using Microsoft Fabric as the anchor platform, Nihilent prepared a target architecture that combined lakehouse and modular design principles to support scalability, performance, and governed self-service analytics.

Transition Roadmap and Technology Change Plan

Nihilent defined a phased transition roadmap that outlined consolidation of existing warehouses and cubes, necessary technology changes, and steps to re-platform and modernize data assets on Fabric.

Key Results & Outcomes

Unified Data Strategy And Roadmap

The client gained a clear enterprise data strategy and transition plan that aligns technology choices with business priorities and future analytics needs.

Rationalization Of Data Warehouses And Cubes

A strategic roadmap was defined to consolidate multiple data warehouses and OLAP cubes into a unified architecture that improves performance and optimizes cost.

Insight Into Optimization Opportunities

The assessment surfaced opportunities to streamline ETL, simplify semantic models, and standardize reporting workloads using a scalable, modular architecture.

Lakehouse-Ready Architecture On Fabric

Redesigned and re-engineered data assets were planned to leverage a Microsoft Fabric lakehouse and modular architecture, positioning the client for enhanced scalability and performance.

Future-Ready Data Ecosystem Vision

The engagement delivered a blueprint for a future-ready data ecosystem that can support evolving BI, analytics, and AI requirements across the food manufacturing portfolio.

Key Takeaways

For a leading African food manufacturer with multiple brands and divisions, the first step toward data modernization was not a large-scale migration project, but a focused enterprise data strategy that clarified where to go and how to get there. By rigorously assessing current data and BI assets, defining business-aligned analytics requirements, and designing a Microsoft Fabric lakehouse architecture with a phased transition roadmap, Nihilent helped the organization move from a fragmented data landscape to a clear, executable vision for a modern, future-ready data ecosystem.

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