Advanced ETL Framework for Applying Graph Analysis on Heterogeneous (Big) Data

Project

Advanced ETL Framework for Applying Graph Analysis on Heterogeneous (Big) Data

Principal Investigator

Dalila Chiadmi

Mohammedia School of Engineering, Mohammed V University, Rabat, Morocco

Oracle Principal Investigator

Hassan Chafi, Vice President, Research and Advanced Development
Sungpack Hong, Senior Research Director

Summary

The objective of this project is to develop an ETL framework for in-memory property graph creation out of different types of data set such as structured (relational data set), semi structured (CSV, XML and JSON) and unstructured data (logs and twitter streams). Eventually, the framework will evolve into a package for building a graphs from multiple, heterogeneous data sources.

 

Our framework will be implemented in such a way that it can be integrated with the existing oracle graph analysis products, such as Oracle Big Data Spatial and Graph. This will provide significant benefits to Oracle customers, by allowing applying graph analysis to any type of structured, semi-structured or unstructured data.