DataOps
DataOps is a methodology that focuses on streamlining the data lifecycle, from data ingestion and processing to delivery and management, ensuring data is accurate, accessible, and timely. It emphasizes automation, collaboration, and integration across data engineering, operations, and analytics teams to improve data quality, speed up data delivery, and reduce the time to insight. By implementing continuous integration and deployment (CI/CD) practices for data workflows, DataOps enhances the efficiency and reliability of data operations, enabling organizations to better leverage their data assets for decision-making and innovation.
Mohamed Ali Hadj Taieb
Assistant professor
My research interests include semantic similarity, semantic relatedness, knowledge representation, Big Data, social media, data management systems and graph embedding.
Mohamed Ben Aouicha
Associate professor
My research interests concern information retrieval, semantic technologies, social media analytics, knowledge representation, Big Data and graph embedding.