Introducing the Time Series Buying Guide for IIoT
All machinery and equipment, including their controls and sensors, tell a story through the data they collect. This data, known as Industrial Internet of Things (IIoT) data, provides a detailed narrative about machines, offering actionable insights to improve operations. IIoT data empowers businesses to optimize and enhance industrial processes by detailing operational status, performance metrics, usage patterns, health diagnostics, and environmental conditions.
The Value of Leveraging IIoT Data
Harnessing IIoT data can significantly improve operational and business efficiency. When fully utilized, it transforms raw information into tangible benefits, such as:
- Real-time anomaly detection and intervention
- Maximized productivity, minimized waste, and downtime
- Reduced unplanned outages and improved maintenance forecasting
Extracting the full value from machines, equipment, industrial controls, and sensor data drives increased revenue by reducing outages, optimizing processes, and lowering error rates. Achieving these benefits requires tools that preserve and enhance dataset quality, ensuring they remain actionable and accurate.
The Challenges of Managing IIoT Data
IIoT data captures changes over time, from subtle fluctuations to catastrophic shifts. This temporal context makes it “time series” data—a sequence of data points collected or recorded at regular intervals. Managing time series data poses unique challenges due to its scale, speed, and complexity:
- Massive scale: Continuous high-speed, high-volume data streams
- Real-time action: Immediate analysis and response within data streams
- Data cardinality: High numbers of tags collected result in high cardinality, which can strain system performance
Businesses can easily generate billions of IIoT time series data points per second, demanding ingestion and storage solutions that can keep pace with real-time analytics.
Why High-Fidelity Data Matters
Successfully managing these challenges results in high-fidelity data—complete and accurate datasets that provide precise insights. High-fidelity data enables businesses to:
- Detect issues early
- Build accurate analytics
- Create reliable models
Conversely, failing to address these challenges results in incomplete datasets, which lack the necessary precision to capture early-stage anomalies or build actionable insights.
Safeguard and Maximize Value from Your Data
The “Time Series Buying Guide for IIoT” explores how manufacturers can identify the tools and architectural practices necessary to achieve high-fidelity datasets. Readers will gain insight into:
- The unique characteristics of IIoT time series data compared to other data types
- Tools that maximize the value of IIoT data
- Pitfalls of certain tools that may seem beneficial but prove detrimental over time
Additionally, the guide offers practical advice on seamlessly integrating specialized IIoT tools into existing architectures, eliminating the need for costly, large-scale system overhauls.
Download the “Time Series Buying Guide for IIoT” now.
