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505 results on '"Hijazi A"'

13. Challenges of Artificial Intelligence in Medicine.

Author

Nida Nasir, Mohammad Al-Shabi, Nabeel Al-Yateem, Syed Azizur Rahman, Muhammad Arsyad Subu, Heba Hesham Hijazi, Fatma Refaat Ahmed, Jacqueline Maria Dias, Amina Al-Marzouqi, Mohammad Yousef Alkhawaldeh, Mohannad Eid AbuRuz, and Ahmad Rajeh Saifan

Published
2023
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32. Big Data and Knowledge Management: A Possible Course to Combine Them Together

Author

Hijazi, Sam

Abstract

Big data (BD) is the buzz phrase these days. Everyone is talking about its potential, its volume, its variety, and its velocity. Knowledge management (KM) has been around since the mid-1990s. The goals of KM have been to collect, store, categorize, mine, and process data into knowledge. The methods of knowledge acquisition varied from organizational culture to the next. Typical processes converted data into information through traditional databases and then applied business intelligence and data mining methodologies to extract knowledge. With the recent arrival of big data as a disruptive technology and the center of big data, this paper attempts to combine KM and BD fields together. Both areas could help each other tremendously. KM historically, when applied correctly, has helped managers to make decisions faster and better, prevented reinventing the wheel, preserved some talented processes through keeping track of best practices, and prompted innovation due to knowledge sharing and dissemination. BD deals with massive amount of data and does not require a traditional database to be effective. BD has its tools and requirement that can be enhanced through KM. The final aim of this paper is to recreate a model where both big data and knowledge management coexist. The author hopes with a better understanding of both fields to develop a new course where the focus is a productive intersection of knowledge management and big data. To keep up with changing times, this paper will bring the needed awareness of these fields for information systems and business students. [For the full proceedings, see ED575713.]

Published
2017

33. Keeping up with Big Data--Designing an Introductory Data Analytics Class

Author

Hijazi, Sam

Abstract

Universities need to keep up with the demand of the business world when it comes to Big Data. The exponential increase in data has put additional demands on academia to meet the big gap in education. Business demand for Big Data has surpassed 1.9 million positions in 2015. Big Data, Business Intelligence, Data Analytics, and Data Mining are the four main branches of data analysis. These areas intertwine, overlap, and clearly depend on each other. This study endeavors to examine the concepts, tools, and techniques of these topics through an introductory class in Big Data. After serious efforts and examination, this study found Data Analytics to be the most suitable topic. One main reason for making this choice included the need to teach the students how to ask questions when they manipulate large amounts of data. The other reason is the availability of PowerPivot and DAX as an Add-In to MS Excel. Most students are familiar with MS Excel, since it is readily available to them. The tools, the techniques, the built-in functions, PivotTables, and DAX, as a formula language, will allow students to experiment with a million rows of data resulting in a rich and rewarding learning environment. The class will also cover the other areas of Big Data and their relationships. Students should become Big Data literate by the time they finish the class successfully. [For full proceedings, see ED570898.]

Published
2016

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