How Data is Rebuilding Manufacturingfrom the Edge Up
An industry conversation with Snowflake and InfluxData on the future of manufacturing intelligence
Key Industry Insights
From 'What happened?' to 'What's likely to happen next—and how can we adapt now?'
Without proper context, moving raw data from edge to cloud just shifts the swamp
Real-world use cases determine where intelligence should reside—edge or cloud
Data is the blueprint for building better products and more efficient systems
Edge vs Cloud: A Use-Case First Approach
Edge: Vision-Based Quality Control
High-speed production monitoring requires millisecond decisions that must happen at the edge, close to machines.
Cloud: Cross-Plant Benchmarking
Analyzing long-term trends and comparing performance across multiple plants leverages cloud-scale analytics.
Hybrid: Modern Data Architecture
Real-time insights at edge combined with broader analytics in cloud - collaboration, not competition.
Expert Insight
"Real-world use cases determine where the intelligence should reside. Edge and cloud are not competitors but collaborators in a data-centric architecture."
From Digital Twins to Physical Intelligence
Reactive Data
- What went wrong?
- After-the-fact analysis
- Scattered information
- Root cause tracing
Digital Twins
- Virtual replicas
- Digital modeling
- Simulation capabilities
- Industry 4.0 foundation
Physical Intelligence
- Active participants
- Real-time decisions
- Continuous learning
- Intelligent ecosystems
The Evolution of Manufacturing Questions
Core Technologies
Time Series Data
The language of machines, capturing every sensor reading, status change, and anomaly as it happens in manufacturing systems.
Apache Parquet & Iceberg
Open standards that integrate natively with Lakehouse architectures, eliminating custom ETL pipelines.
Hybrid Data Architecture
Bridging edge intelligence with cloud-scale analytics to move data fluidly for the right use case.
Contextualized Data
Without proper context, moving raw data from edge to cloud adds no value—it just shifts the swamp.
Edge Intelligence
Real-time insights and sub-second decision-making happening close to machines for critical operations.
Interoperability Standards
Open formats enable manufacturers to store, share, and analyze data across platforms, reducing friction.
A Collaborative Future for Industrial Intelligence
InfluxData Platform
Handles collection and initial processing of time series data, often at the edge
- Time series data collection
- Edge processing
- Apache Parquet format
- Real-time insights
Snowflake Platform
Serves as scalable cloud platform where data is integrated, modeled, and analyzed
- Cloud-scale analytics
- Data integration
- Cross-plant benchmarking
- Machine learning
Collaborative Benefits
Data Integration
Platforms work together to move data fluidly
Reduced Friction
Open standards eliminate custom ETL pipelines
Use-Case Driven
Intelligence resides where it's most effective
Interoperability
Manufacturers can analyze data across platforms
Start With the Data
"It's no longer just a byproduct of operations—it is the blueprint for building better products, more efficient systems, and more resilient enterprises."