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Ep 39 DataOps for Digital Transformation In Manufacturing - [ Aron Semle, CTO Highbyte]
DataOps for Digital Transformation In Manufacturing. In this episode, Kudzai Manditereza interviews Aron Semle, the CTO of Highbyte. HighByte is an industrial software company founded in 2018 with headquarters in Portland, Maine USA. The company builds solutions that address the data architecture and integration challenges created by Industry 4.0. HighByte Intelligence Hub, the company’s award-winning Industrial DataOps software, provides modeled, ready-to-use data to the Cloud using a codeless interface to speed integration time and accelerate analytics.
Outline
✅ What is DataOps, and Why is it relevant for Digital Transformation?
✅Key Steps of Implementing DataOps for a digital transformation strategy.
✅ The Role of DataOps in a Unified Namespace Architecture
✅Typical Data Sources for Integrating into DataOps Pipeline
✅ Effective practices for modeling, normalization, and contextualization of Industrial data.
✅ Data Modeling Standards for DataOps, Pros, and Cons
✅The role of MQTT and Sparkplug in a DataOps-based Strategy
✅ The role of OPC UA in DataOps Strategy
✅ DataOps for Historical Data in the Unified Namespace
✅ REST API for real-time and transactional data harmonization
✅ Best practices for DataOps deployment
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By Kudzai Manditereza
5
11 ratings
DataOps for Digital Transformation In Manufacturing. In this episode, Kudzai Manditereza interviews Aron Semle, the CTO of Highbyte. HighByte is an industrial software company founded in 2018 with headquarters in Portland, Maine USA. The company builds solutions that address the data architecture and integration challenges created by Industry 4.0. HighByte Intelligence Hub, the company’s award-winning Industrial DataOps software, provides modeled, ready-to-use data to the Cloud using a codeless interface to speed integration time and accelerate analytics.
Outline
✅ What is DataOps, and Why is it relevant for Digital Transformation?
✅Key Steps of Implementing DataOps for a digital transformation strategy.
✅ The Role of DataOps in a Unified Namespace Architecture
✅Typical Data Sources for Integrating into DataOps Pipeline
✅ Effective practices for modeling, normalization, and contextualization of Industrial data.
✅ Data Modeling Standards for DataOps, Pros, and Cons
✅The role of MQTT and Sparkplug in a DataOps-based Strategy
✅ The role of OPC UA in DataOps Strategy
✅ DataOps for Historical Data in the Unified Namespace
✅ REST API for real-time and transactional data harmonization
✅ Best practices for DataOps deployment