Extract and manage machine data from one central interface available for projects all across your organization.
- Collect data from machines, sensors, and other sources
- Standardize and consolidate incoming data streams
- Full transparency from the edge to the cloud
- Direct data insights
- Easy-to-use interface
Data pods - this is where you pull and analyse edge and cloud data. Each pod comes with built-in infrastructure for powerful IoT analytics.
- Lightweight
- Decentralized
- Multipliable
- Fully autonomous
- Flexible storage capacities
Extract edge data
- Collect raw data from multiple sources
- Overview of loaded data
- Automated data type detection
- Manual adjustment
- Fully managed data package logistics
Develop AI in data science workbooks
- Custom queries with SQL or Python
- Markdown along the code
- Direct use of all pod CPUs
- PostgreSQL database and TimescaleDB extension
Analysis & visualization
- Custom infographics
- Custom interactive elements
- Embedded visualizations with near real-time updates
From ingesting data to complex analyses - the process is seamless.
Integrations - here is an overview.
Business Intelligence
Business Tools
Data Science
Explore blog resources
If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture.
Today’s unprecedented levels of heterogeneity, volume, and connectivity call for IoT data management strategies that consider scale, data gravity, and integration.
The use of Wireless Sensor Networks (WSN) in a variety of (Industrial) Internet of Things scenarios has gained popularity over the past years.