Background:
A mid-size manufacturing company, owned by private equity, experienced significant growth through both organic expansion and mergers and acquisitions. This rapid growth led to a complex and fragmented data landscape, with multiple on-premises MS SQL databases spread across the organization. The company faced several challenges:
Data silos: Different departments operated in isolation, with limited access to shared data.
High operational costs: Upgrading and maintaining multiple on-premises systems was costly.
Limited insights: The company struggled to gain advanced insights from its data due to infrastructure limitations.
Goals:
Eliminate Data Silos: Consolidate data sources to foster collaboration and enable holistic insights across departments.
Leverage Azure Fabric: Utilize Microsoft Azure Fabric's scalability and manufacturing-specific features to enhance operations.
Reduce Operational Costs: Optimize infrastructure spending and reduce the overhead related to system upgrades and security management.
Solution:
The company embarked on a 12-week migration to Microsoft Azure, focusing on creating a unified and scalable data platform.
Data Consolidation: Migrated all on-premises MS SQL databases to Azure Fabric, creating a centralized platform for all data.
Scalability: Azure Fabric’s scalable architecture allowed the company to handle increasing data volumes with ease, aligning with future growth.
Results:
Data Silos Eliminated
By centralizing their data on Azure Fabric, the company broke down internal silos. Different departments could now access the same data, enabling better collaboration and faster decision-making across the organization.
Operational Cost Reduction
Upgrades and Security Patches: With Azure Fabric’s managed services, the need for manual upgrades and security patching was eliminated, reducing operational overhead.
Cost Savings: Leveraging Azure’s pay-as-you-go pricing model, the company significantly cut infrastructure costs compared to maintaining multiple on-premises systems.
Advanced Insights with Azure Machine Learning
The company integrated Azure Machine Learning with their new data infrastructure, enabling advanced analytics such as predictive maintenance and anomaly detection.
These insights helped optimize production processes and improve supply chain management, resulting in reduced downtime and enhanced operational efficiency.
Conclusion:
The migration to Microsoft Azure Fabric transformed the company’s data management strategy, enabling them to centralize their data, reduce operational costs, and unlock advanced analytics capabilities. The transition positioned them for long-term growth, improved efficiency, and more data-driven decision-making across the organization.
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