of organizations lack an enterprise data strategy to fully capitalize on their data assets.
Accenture
In today’s data-driven landscape, a strong data strategy is essential for organizations to leverage the most out of their data value chain. Organizations who are focusing on the tail-end of the chain by embracing data exchange platforms, thrive more than others.
Access
Data
Value
Data
Connect
Data
Protect
Data
Share
Data
Manage
Data
Monetize
Data
Get Value out of Data
Central to executing this strategy is the ability to effectively analyze and share data.
Acentrik being the integral part to an organizations’ data strategy, helps unlock greater value from data with privacy-preserving features that enable secure data exchanges, while ensuring full data privacy.
Predictive maintenance can increase labor productivity by up to 20% and reduce inventory levels and carrying costs by up to 10-30%.
Maximizing equipment efficiency and lifespan through data-driven predictive maintenance.
Enhanced labor productivity: Optimizing maintenance schedules and reducing downtime, allowing maintenance teams to focus on preventative measures rather than reactive fixes.
Inventory optimization: Accurately predicting when parts and materials are needed, thus streamlining inventory management and reducing excess stock and associated costs.
Secure computation at source
Acentrik enables secure sharing and computation of equipment sensor data across data hubs while keeping data at source, optimizing maintenance schedules and enhancing labor productivity without compromising data privacy.
Data aggregation across silos
Acentrik enables the aggregation of maintenance data from regions like APAC and EU without moving the data, providing greater insights in cost efficiencies by accurately predicting parts needs and reducing inventory excess.
Our platform is infra and industry agnostic, enabling global organizations to integrate into their existing infrastructure and implement their data strategy seamlessly.
From
Data Hub A
From
Data Hub B
From
Data Hub C
From
Data Hub D
Use Case 1
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Use Case 3
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