Solving Data Challenges: Olameter and Onehouse Team Up for Enhanced Predictive Maintenance
Blog post from Onehouse
Olameter, a leader in utility asset management, faced significant challenges in processing large volumes of XML data from electricity meters and transformers to predict outages, which initially took over six months for a year's worth of data due to inefficient custom .NET applications. To address this, they partnered with Onehouse, which developed a custom XML ingestion solution using Apache Hudi™ that enabled Olameter to process data incrementally and efficiently, reducing processing times from years to days. This collaboration also involved optimizing data structures for faster querying and analysis by flattening nested data and using geo-spatial clustering. Beyond data processing, Onehouse supports Olameter in building downstream pipelines and machine learning models, enhancing operational insights and service reliability. The partnership has allowed Olameter to achieve near real-time XML ingestion, significantly improve infrastructure management, and advance predictive maintenance capabilities, ultimately increasing quality of service and customer satisfaction in the utilities sector.
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