Big Data Challenges in Information Engineering Curriculum

The amount of accumulated data is growing at unprecedented rates. This data is mainly unstructured or semi structured and comes from different sources in a variety of forms. Recently, a range of supporting storage and distributed parallel computing technologies have been developed and put into use by the sector. The products and implementations include; Apache's Hadoop, data processing framework Map Reduce, distributed big data management system Cassandra and other NoSQL database and data storage systems. Among the major challenges are; data representation, reliable shared storage, efficient algorithms and scalable distributed HW/SW infrastructures. Surprisingly, current curricula lack the necessary components to create awareness and a good understanding of these state of the art concepts and technologies. There is an urgent need for integrating the developments in big data technologies into the educational programs and computing curricula. This need not only is dictated by the industry, but also by the employement dynamics in the related professions. This paper discusses fundemental big data issues and technologies that are considered to be necessary for the existing educational programs in computing, information systems and information engineering areas.