Custom Analytics with Edge Data
Consolidate data from multiple sources and create sophisticated data science projects for your analytics requirements
Powerful Analytics for All Your Edge and Cloud Data
Deploy a dedicated data pod for each analytics project
Leverage scalable, dedicated cloud computing resources for each data pod to tackle even the most advanced data science tasks. Automate data collection from your fleet apps and seamlessly integrate it with other cloud data, enabling powerful custom analytics.
Develop AI in data science workbooks
Create custom queries and data transforms with SQL or Python within each data pod. Train AI models and document your work with Markdown along with your code.
Create custom visualizations with infographics
Leverage sophisticated custom embeddable infographics with HTML and JavaScript code pens served right from the data pods.
New birds, welcome to the flock!
Features
From ingesting data to complex analyses - the process is seamless
Use the latest data science libraries
Use the preinstalled Python libraries like pandas, polars, pytorch or scipy for your custom data science and analytics.
TimescaleDB as foundation
Data pods are based on PostgreSQL and TimescaleDB. Create new data pods for different projects with different resources, automatic point-in-time database backups.
Dedicated storage & compute capacities
Zero shared resources between data pods ensure stable performance for the most demanding workloads right out of the box.
Interface with any BI tools
Integrate with your favorite BI tools like PowerBI, Tableau or Qlik to combine and present data in your existing BI environment.
Provide API access to your prepared data
Other services can consume your aggregated and transformed data through an API interface secured by fine-grained access control keys.
Use data-driven and scheduled execution
Your data transformations can be executed based on incoming new data or by a time schedule.