EarthLab Luxembourg proposes you a state of the art catalogue of technologies and tools. We will take care of you by making your experience simple and efficient.
We have designed our platform to host large amounts of data and apply real-time or batch algorithms. We have considered regulations, cyber security best practices and ICT policies to make possible the integration into your existing infrastructure of our solutions allowing the use of your local data with on-premises resources.
Technologies
Apache Mesos Ecosystem
Used as data-centric cluster management, Mesos provides efficient resource isolation and sharing across distributed applications with fine-grained resource allocation, improving cluster utilization.
Apache Spark
Apache Spark is a powerful open source processing engine built around speed, ease of use, and sophisticated analytics. Thanks to parallel and in-memory treatments, it provides unprecendented performances.
TensorFlow
TensorFlow is a computing library for machine learning in various kinds of perceptual and language understanding tasks. Associated with Keras, it is commonly used in our platform to implement Deep Learning Analysis.
Cassandra
Cassandra is a distributed database solution for tabular and time-series information (Macro-Economic information, Stock Exchange, Internet of Things, existing datasets...).
ElasticSearch
ElasticSearch is a document oriented storage solution. It permits to store large descriptive sets of documents (e.g. JSON files) with very powerful search and filter capabilities including geo-queries.
Understand from the past to efficiently act and predict the future
We anticipate that data sources and their collection will be multiplied and considered as basic raw material. The access points will be much simpler for non-experts and visualisation tools will still continue to grow rapidly.
The needs of the end users will therefore evolve and the players who will have their place in the game will be those who will combine effectively services and solutions responding to the current barriers: massive processing of the data to extract immediate and large-scale value, limit the constraints of integration into third-party architectures, factual correlations between business drivers and spatial data evidence.
In summary, we believe that platforms combining latest technological developments, artificial intelligence, Big Data and interoperability will standardise and bring a new definition of data centric applications and a new community of users.