Modern Data Platform on Azure Databricks
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.
Context: Need to modernise a legacy, siloed data estate to enable scalable, enterprise-wide analytics.
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.
A Lakehouse with Medallion Architecture was implemented on Databricks, enabling cross-domain data use, unified access, and integration across previously siloed systems.
Key processes were refactored to reduce manual effort, pipelines were optimised for speed and reliability, and errors in data processing were eliminated.
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.
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.
DevOps pipelines were implemented to standardise builds and deployments, and financial operations processes were implemented to improve control and visibility of spend.
Scalable analytics foundation established, enabling cross-domain insights and future advanced analytics.
Trusted data products delivered, providing reliable, certified information across core business areas.
Operational efficiency and performance improved: automated pipelines reduced manual effort and errors.
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.”
Talk to our team about building a governed lakehouse on Azure Databricks that the whole business can trust.