For KSB, we developed a web application that efficiently processes large amounts of IoT data and make it accessible via intuitive visualizations. Targeted analysis and data labeling facilitate data-driven decisions for their support teams while also providing optimal aid for training machine learning models.
- Big Data, Data Visualisation, ML Training
Projekt
Visualized Data, Smarter Models
Challenge
Big Data and Real-Time Analysis
KSB faced the challenge of capturing and aggregating massive IoT datasets in real-time to gain exploitable insights. The implementation of visualizations and machine learning was crucial to unleash the full potential of this data.
Solution
Scalable Web App With Machine Learning
Our solution focused on the following key areas:
- Big Data Management
Overcoming the challenges of real-time accessibility and aggregation of large IoT datasets. - Visualization and ML Integration
Data visualization and the integration of machine learning enabled dynamic feedback and model training. - Collaborative Development
Through close collaboration with KSB, we achieved seamless integration of frontend components and strengthened cross-team capabilities.
Result
Optimized Data Analysis and Machine Learning
Our web app enabled KSB to perform advanced data analytics and integrate machine learning. This optimized decision-making processes and gave KSB a competitive advantage via faster and more informed insights into their data.
Starting from the backend architecture in AWS to data connectivity and user management they handled everything with great experience and knowledge. They set a reliable base for the development of future features in the MDC.
Tobias Klunke · Director Machine Diagnostics · KSB SE & Co. KGaA
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