Biography: IBM Big Data Specialist

Prof. Dr. Mostafa Ezziyyani, IEEE and ASTF Member received the “Licence en Informatique” degree, the “Diplôme de Cycle Supérieur en Informatique” degree and the PhD “Doctorat (1)” degree in Information System Engineering, respectively in 1994, 1996 and 1999 from Mahmmeed V University in Rabat, Morocco. Also, he received the second PhD degree “Doctorat (2)” in 2006, From Abdelmalek Essaadi University” in Distributed Systems and Web Technologies. In 2008 he receives a Researcher Professor Ability Grade. Now he is a full professor of Computer Engineering and Information System in Faculty of Science and Technologies of Abdelmalek Essaadi University since 1996.

  • My research activities focus on the modelling databases and integration of heterogeneous systems (with the various developmennts to the knowledge base, the object BD, active BD, Big-Data, Web semantic, Security, DataCenter, Optimisation, Dataminig, Multi- System Agents, distributed systems and mediation).

research areas

  • Database Engineering

    Motivation and objectives Database engineering is just one step in the information system life cycle. Indeed, painfully recovering the specifications of a database is not a sufficient motivation per se. It is generally intended to redocument, convert, restructure, maintain or extend legacy applications. Here follow some of the most frequent objectives of database engineering :
    • DATA Maintenance
    • DATA Transmission
    • DATA Migration
    • DATA Integration
    • DATA Extraction
    • DATA Conversion
    • DATA Administration
    • DATA Analysis
    • DATA Protection.

  • Big Data, Data Warehouse and Data Mining

    Data warehousing systems were conceived to support decision making within organizations. These systems homogenize and integrate data of organizations in a huge repository of data (the data warehouse, Big Data) in order to exploit this single and detailed representation of the organization and extract relevant knowledge for the organization decision making.
    In a broad range of application areas, data is being collected at an unprecedented scale. Decisions that previously were based on guesswork, or on painstakingly handcrafted models of reality, can now be made using data-driven mathematical models. Such Big Data analysis now drives nearly every aspect of society, including mobile services, retail, manufacturing, financial services, life sciences, and physical sciences. Data visualization is becoming an increasingly important component of analytics in the age of big data

  • Integration of heteregeneous systems

    A common problem facing many organizations today is that of multiple, disparate information sources and repositories, including databases, object stores, knowledge bases, le systems, digital libraries, information retrieval systems, and electronic mail systems. Decision makers often need information from multiple sources, but are unable to get and fuse the required information in a timely fashion due to the difficulties of accessing the different systems, and due to the fact that the information obtained can be inconsistent and contradictory. The goal of the processus of integration of heteregeneous systems is to provide tools for accessing, in an integrated fashion, multiple information sources, and to ensure that the information obtained is consistent.

  • Knowledge management process

    The rise of the knowledge economy and the socio-economic transformation of societies have resulted in knowledge being the fundamental means of wealth and prosperity. Hence, leveraging knowledge resources effectively and efficiently is vital in order to gain a competitive advantage and to ensure the sustainable development for societies, as well as for the organizations.
    Managing knowledge efficiently and effectively is considered a core competence for organizations to survive in the long run. The capability of organizations to leverage their knowledge resources seems to be one of the most important parameters from the strategic perspective. Nevertheless, the evolution and implementation of Knowledge Management (KM) is still in progress, leading to the difficulty in composing a comprehensive and applicable KM framework for organizations.

Basic Teaching

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