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How to Build Scalable Data and AI Industrial IoT Solutions in Manufacturing

📅 Date:

✍️ Authors: Bala Amavasai, Vamsi Krishna Bhupasamudram, Ashwin Voorakkara

🔖 Topics: IIoT, manufacturing analytics

🏢 Organizations: Databricks, Tredence


Unlike traditional data architectures, which are IT-based, in manufacturing there is an intersection between hardware and software that requires an OT (operational technology) architecture. OT has to contend with processes and physical machinery. Each component and aspect of this architecture is designed to address a specific need or challenge, when dealing with industrial operations.

The Databricks Lakehouse Platform is ideally suited to manage large amounts of streaming data. Built on the foundation of Delta Lake, you can work with the large quantities of data streams delivered in small chunks from these multiple sensors and devices, providing ACID compliances and eliminating job failures compared to traditional warehouse architectures. The Lakehouse platform is designed to scale with large data volumes. Manufacturing produces multiple data types consisting of semi-structured (JSON, XML, MQTT, etc.) or unstructured (video, audio, PDF, etc.), which the platform pattern fully supports. By merging all these data types onto one platform, only one version of the truth exists, leading to more accurate outcomes.

Read more at Databricks Blog