Brief description: 

Radiatus platform main goal is to provide to the end-user a BDAaaS (Big Data Analytics as a Service) solution in the Cloud. This platform aims to allow the end-user to focus on the data analysis processing, and provides the necessary level of abstraction about the details of configuration, services, adaptability and deployment, making it transparent the selection of the IaaS (Infrastructure as a Service). Radiatus can be represented by a set of abstract layers: input data, streaming acquisition, distributed processing, distributed storage and output data:

  • Input data represents the data to be introduced into the platform, which can be obtained from a distributed set of sensors or from a user processing interface where, in addition, analytics algorithms can be selected by data scientists.
  • Streaming layer manages the constant stream of data from sensors which allows both a processing in real-time through the distributed processing phase and a persistent storage in the distributed storage for a post processing.
  • Analysis results as output of the distributed processing can be presented in the user processing interface (output data), as well as stored in the distributed storage or transmitted in stream (output data) through the streaming layer.
  • The information in the distributed storage can be retrieved for a data analysis in batch or used from the user processing interface or this information can be accessed directly from external entities through a REST (Representational State Transfer) API designed to manage the output data.

 

Main Features: 
  • An elastic platform environment for Big Data Analysis in the cloud without the need for extra investment in hardware resources
  • Inmediate access to Big Data Analytics services without the need to make expensive investments in infrastructure, with consequent cost savings. Cloud solutions also make it easier to pay for the resources that are actually used at all times
  • The analysis, design and implementation of a Big Data Analytics service in the cloud (cloud) for processing data acquired in streaming, adding the complexity of real-time data analysis
Areas of Application: 

Big Data analytics can provide high value to companies because of the knowledge they can obtain from the huge amount of data generated and collected . This knowledge and value have a very broad applicability, from predictive maintenance or the optimization of machines configuration (generating cost savings and strategic advantages for the industry) to the analysis of customer behavior that allow a better adjusting of the supply to the demand, increasing the value of offered goods and services. 

  • Predictive maintenance
  • Identification of consumer trends
  • Optimization of industrial process parameters
Customer Benefits: 

Radiatus platform will allow users and companies, and more specifically SMEs, to abstract from the complexity of Big Data infrastructure management, and to focus on the task of data analytics, also at a reasonable cost.  Big Data Analytics could be applied to different and relevant company aspects, such as predictive maintenance, optimization of machine configuration, customers trending analysis, etc . More specifically, among the different advantages that the use of Big Data Analytics as a cloud service, it is worth mentioning the following: access to many resources without great investments, smart managment of the elasticty, agnostic access  to IaaS, and quick deployment of the solution. This approach is relevant with very computing and storage resources demanding applications, and costly solutions in terms of configuration and deployment:

  • Cost reduction
  • Mobility
  • Pay per use
  • Technoloy independence
  • Scalability and elasticity
  • Security

 

Workflow: 
Published
Platform / Framework

Owner

Instituto Tecnológico de Informática (ITI)
Valencia
Spain
Type: 
BDVA member
Contact: 
BDV Reference categories: 
Data Analytics
Data Management
Data processing architectures
Data Protection
Data Visualisation and Interaction
Readiness Level: