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Omnia
Case Study Chemicals Azure Databricks

Transforming fragmented legacy systems into a scalable, trusted foundation for analytics and data‑driven decision‑making

Modern Data Platform on Azure Databricks

9/10
Out of 10 Net Promoter
Score (NPS)
Client
Omnia
Industry
Chemicals: Mining and Agriculture
Location
South Africa
Employees
~3,800
Delivery
2-3 years (phased rollout)
01 · Customer Profile

About Omnia

Omnia Holdings Limited is a JSE-listed, South Africa-headquartered diversified chemicals group operating across Agriculture, Mining, and Chemicals, with an established manufacturing and distribution footprint across Africa and select international markets.

Omnia needed to modernise a legacy, siloed data estate that was limiting visibility and slowing decision-making. The objective was to establish a scalable, enterprise-wide analytics platform that enables governed access to trusted data, supports advanced insight generation, and creates a foundation for consistent, organisation-wide intelligence.

The Context

Context: Need to modernise a legacy, siloed data estate to enable scalable, enterprise-wide analytics.

02 · Challenges

What Was Holding Insight Back

01Legacy and fragmented systems limiting scalability and enterprise-wide insight.

02Siloed data with minimal integration across business units.

03Manual, time-consuming processes slowing reporting and decision-making.

04Frequent errors and inconsistencies undermining trust in data.

05Limited analytics capability restricting advanced insights and predictive decision-making.

03 · Solution

How Decision Inc. Delivered

Azure Databricks · Medallion Architecture · Genie
decision-inc / omnia / solution
solution --module 01

Modern, Scalable Data Architecture

A Lakehouse with Medallion Architecture was implemented on Databricks, enabling cross-domain data use, unified access, and integration across previously siloed systems.

DatabricksLakehouseMedallion Architecture
solution --module 02

Automated and Reliable Data Pipelines

Key processes were refactored to reduce manual effort, pipelines were optimised for speed and reliability, and errors in data processing were eliminated.

Refactored processesSpeedReliability
solution --module 03

AI Enablement

AI capabilities were introduced using Genie to generate insights over curated, trusted data, with the further goal of enabling a self-service BI model for broader enterprise use.

GenieCurated dataSelf-service BI
solution --module 04

Data Quality and Governance

A data quality framework with automated checks was established for master data management, sensitive data was classified for governance, and certified data products were delivered.

Data quality frameworkMaster dataCertified data products
solution --module 05

Operational Excellence

DevOps pipelines were implemented to standardise builds and deployments, and financial operations processes were implemented to improve control and visibility of spend.

DevOpsFinancial operationsSpend visibility
9/10Net Promoter Score (NPS)
3Business divisions: Agriculture, Mining and Chemicals
2-3 yrsPhased rollout
~3,800Omnia employees
04 · Results

What Omnia Now Has

Foundation

Scalable analytics foundation established, enabling cross-domain insights and future advanced analytics.

Trust

Trusted data products delivered, providing reliable, certified information across core business areas.

Efficiency

Operational efficiency and performance improved: automated pipelines reduced manual effort and errors.

Governance

Formal data quality governance implemented, ensuring consistent, accurate data to support confident decision-making and scale analytics adoption.

“The reality is that moving away from legacy, fragmented systems is never straightforward. This solution has provided a solid foundation, transforming how we work with data and positioning us as an insight-driven organisation. There is still more to do, but we are confident we have the capabilities to succeed today and scale into the future.”
Gert Van der Walt
Head of Data & Analytics, Omnia
Solution Used

The Technology

Data PlatformAzure DatabricksCloudMicrosoft AzureAIDatabricks Genie

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