PARTNERSHIP ANNOUNCEMENT

KloudPortal Partners with Databricks

Empowering Customer Growth with Next-Gen Data Solutions

Together, KloudPortal and Databricks help organizations unify their data, accelerate innovation, and drive measurable business outcomes.

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From Plant Data Silos to Predictive Maintenance

How a leading steel & metals manufacturer moved from fragmented on-premises operational data to a cloud-based Data + AI foundation — and enabled predictive maintenance for 50 critical motors.

50

Critical Motors

Pilot scope

On-Prem → Cloud

Operational data migration

Unified Data Pipelines

Across IT and OT systems

Predictive Maintenance

AI-driven asset insights

The Problem

Critical operational data, but no unified view.

The manufacturer had operational data distributed across on-premise systems, plant controls, instrumentation and maintenance records. This data was difficult to retain, integrate and analyze at scale, making it hard to identify early signs of motor degradation.
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On-Premise Data Silos

Data across multiple systems and locations
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Limited Historical Visibility

Difficult to analyze trends and patterns
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Fragmented Plant Data

Oracle, PLC/SCADA, sensors and maintenance not integrated

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Reactive Maintenance

Reliance on scheduled and reactive intervention

Challenge

The Transformation Challenge

From fragmented on-premise systems to a unified, cloud-based Data + AI foundation.

Before

Fragmented On-Premise Environment
  • database (1)Oracle enterprise systems
  • FactoryPLC / SCADA plant data
  • workflowInstrumentation and sensor telemetry
  • fileMaintenance records and asset history

After

Cloud-Based Data + AI Foundation
  • cloudCloud foundation on AWS, Azure or GCP
  • cloudGoverned Databricks Lakehouse
  • cloudAutomated data pipelines
  • cloudML models, dashboards and alerts

Our Solution

A modern Data + AI solution to unify, analyze and predict.

KloudPortal migrated selected operational data to the cloud, built automated data pipelines, implemented a governed Databricks Lakehouse, and developed predictive maintenance capabilities for 50 critical motors.

Cloud Migration & Foundation

Moved selected on-premises operational data to a secure cloud environment.

Data Engineering

Built automated ETL/ELT pipelines across Oracle, PLC/SCADA, instrumentation and maintenance sources.

Lakehouse & Governance

Implemented Databricks Lakehouse with Delta Lake and Unity Catalog for unified, governed data.

analysis

Predictive Maintenance

Developed ML models to identify abnormal behavior and failure risk for 50 critical motors.

Operationalization

Delivered dashboards and alerts, enabling maintenance teams to monitor, prioritize and take proactive action.

TECHNOLOGY

Technology Approach 

Key technologies used in the engagement (illustrative):
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Illustrative Business Impact.

The solution delivered a strong foundation for predictive maintenance and broader manufacturing analytics.

50 motors

Pilot scope

Unified operational data

Integrated IT and OT data

Earlier anomaly detection

Identify high-risk motors early

Scalable Data + AI foundation

Ready for additional assets, lines and plants

Additional Outcomes (Illustrative)

  • Reduced unplanned downtime potential (measured against baseline)
  • Improved maintenance prioritization and planning
  • Better visibility into asset health and operating conditions
  • Reduced reactive maintenance and emergency interventions
  • Scalable foundation for AI across manufacturing use cases

Predictive maintenance was the business outcome. Data Engineering and Cloud Modernization were the foundation.

— KloudPortal Perspective

READY TO CREATE SIMILAR IMPACT?

Turn plant data into operational intelligence.

Partner with KloudPortal to build your Data + AI foundation for smarter, more reliable manufacturing operations.

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