Accelerating Industrial DataOps to optimize Data Management and IoT Scalability – a catalog of case studies | SPONSORED
IIoT practices are having an impact, but Developers struggle to scale successful AI/ML projects. WHY? Data management is many times the culprit. Industrial OT and Business IT are not the same. For example:
Business data is delivered in batches or transaction records complete with metadata descriptors but lacking synchronous time stamps for correlation.
Industrial OT data is high velocity time-series and event information that lacks the detailed descriptors and features needed to use it outside of operations.
That means the usual IT or OT data management techniques are insufficient for IIoT requirements.
Integrating data from business systems, control systems, historians, maintenance management, and business systems are dramatically increasing situational awareness.
DataOps techniques are improving data management for analytics delivery to increase its operationalization, better support workforce, and overcome supply chain issues.
Real time IIoT is enriching analytics applications. Increased visibility, predictability, and prescriptive powers are taking the guesswork out of decision-making.
Read this short e-book to see how Hitachi customers leverage Industrial DataOps technology to provide greater visibility, better predict operations and optimize work processes.
Download the catalog get access to the following case studies:
- Smart Building and Security for Covid-19
- Power Grid Cabinets
- Smart Poles
- Energy Performance Monitoring on Industrial Plants
- Smart Metering
- Smart Organic Waste Compost Machine
- EV Charging Solution
- Remote Condition Monitoring
- Molding Line Operations
- Ingest / Predictive Maintenance for Smart Space
- Anomaly Detection for Amusement Rides
Sponsored by Hitachi Vantara
Data Retention for Long-Term IIoT Monitoring Using Time Series Databases
Traditional industries have evolved by implementing many Industrial IoT practices, where we can get data from mechanical devices and sensors. Such real-time data monitoring helps perform better analysis, predict equipment failure, and reduce operating costs. However, IIoT creates enormous volumes
Predictive Maintenance in IIoT: Leveraging Time Series Data for Equipment Longevity
The industrial Internet of Things (IIoT) helps bind machines, sensors, and systems together. They form a network of intelligent devices working together to generate and share data. This approach to managing devices has revolutionized how industries manage, monitor, and maintain
Enhancing Manufacturing Processes with AI and Low-Code: An Essential Guide for Modern Manufacturers
IIoT World’s latest booklet, "Enhancing Manufacturing Processes Through AI and Low-Code Integration," is a must-read resource for manufacturers looking to leverage cutting-edge technologies to drive efficiency, innovation, and productivity. This guide delves into the synergy between AI and low-code platforms, offering actionable