Developer FAQs and Resources
How We Are Different
Data Aggregation
Aggregate and synchronize siloed data from sources that have never been aggregated before for enterprise-wide collaboration and a shared big picture view.
Real-Time Data
Analyze and navigate your data in real-time using rich and intuitive visualizations— get real-time alerts so you can act immediately and proactively mitigate risk.
Unmatched Data Set
Enrich your data by tapping into the industry’s most comprehensive live and historic streaming dataset for unmatched operational clarity and proactive risk modeling.
Machine Learning
Apply advanced algorithms to help you detect patterns faster, understand the ‘how’ and ‘why’, and use predictive guidance to make better-informed decisions with machine learning.
How Live Earth Can Help
Utilizing Real-Time Data
Analyze and navigate your data in real-time using rich and intuitive visualizations— get real-time alerts so you can act immediately and proactively mitigate risk.
Dynamic Marketing
Reduce OPEX and dynamically adjust marketing campaign tactics using real-time payment transactions automatically sourced and structured with Live Earth's data streaming platform.
Applying Data Aggregation
Aggregate and synchronize siloed data from sources that have never been aggregated before for enterprise-wide collaboration and a shared big picture view.
Banking Controls
Automatically source and structure siloed systems’ data and use predictive analytics to identify and address anomalies in daily operations.
Leveraging Unmatched Data Set
Enrich your data by tapping into the industry’s most comprehensive live and historic streaming dataset for unmatched operational clarity and proactive risk modeling.
ESG Risk Mitigation
Get real-time notifications of risk, scores, and proactive threats over time through time-series visualizations created via automatic sourcing of siloed ESG data.
Advanced Machine Learning
Apply advanced algorithms to help you detect patterns faster, understand the ‘how’ and ‘why’, and use predictive guidance to make better-informed decisions with machine learning.
Fraud & Anomaly Detection
Detect and react to fraudulent or anomalous activity, understand why the problem happened, and use predictive capability to be ahead of the curve for the next time.
Integrate Custom Data Streams in Real Time
Live Earth allows developers to create geospatial dashboards quickly – with no GIS expertise or special coding required – to render, animate, or visualize data.
Simply stream your raw events to the Live Earth Cloud and they will be stored, correlated with other data streams (weather, traffic, etc.) and available for instant viewing within the Live Earth Windows, iPad, or web-based clients.
- No need to learn a mapping SDK
- Simply push JSON events up to the Live Earth API
- Data is automatically stored, queried, rendered, animated, and visualized as you explore the data in time and space
- Automatically see your data correlated with other out-of-the-box data streams
- Analyze and visualize the data in multiple ways
- Play, pause, or rewind your data
- Create heat maps, measure, create shapes, and more
- Send once - see anywhere
Live Earth is here to take your business to the next level
API Documentation and Specifications
Not only does Live Earth allow you to view items on a map and see them update over time in geospatial dashboards for your team, it also lets you display disparate data streams from various sources in a single unified application.
This documentation explains how to leverage the API. The API is RESTful and uses JSON as the transport mechanism. The list of endpoints can be found below.
[Note: Each endpoint includes a short description of the purpose of the endpoint, the endpoints rl and method (e.g., GET, POST, PUT, DELETE), a fully annotated schema for both the request and response payload, as well as example JSON for the request and response object.]
Documentation to Push Data
[NOTE: For Dev and Trial accounts, we store data for 7 days in our cloud before the data is cleaned up. So, when pushing data, make sure the timestamp in the JSON string is not older than 7 days.]