Faculty of Engineering - Ain Shams University, Home

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Business Intelligence and Big-Data Analytics

What Will Learn?

  • Course Aims
  • Course Goals
  • Decent Work and Economic Growth
  • Industry, Innovation and Infrastructure
  • Sustainable Cities and Communities

Requirements

PHM113s AND CSE334s

Description

  • English Description

    Fundamentals of big data technologies and tools. Structured and unstructured data. Distributed processing ecosystem. Big data storage and analytics. Big data analytics machine learning algorithms. Graph analytics. Big data visualization. Data models. Data cleaning, processing, and analysis algorithms. Big data languages and technologies.
  • Arabic Description

    Fundamentals of big data technologies and tools. Structured and unstructured data. Distributed processing ecosystem. Big data storage and analytics. Big data analytics machine learning algorithms. Graph analytics. Big data visualization. Data models. Data cleaning, processing, and analysis algorithms. Big data languages and technologies.
  • Department
    Computer and Systems Engineering
  • Credit Hours
    2
  • Grades
    Total ( 100 ) = Midterm (20) + tr.Student Activities (30 = tr.Industry 0% , tr.Project 10% , tr.Self_learning 0% , tr.Seminar 20% ) + Exam Grade (50)
  • Hours
    Lecture Hours: 2, Tutorial Hours: 1, Lab Hours: 0
  • Required SWL
    100
  • Equivalent ECTS
    4
  • - Minelli Michael Michele Chambers and Ambiga Dhiraj. 2013. Big Data Big Analytics : Emerging Business Intelligence and Analytic Trends for Today's Businesses. Hoboken New Jersey: John Wiley & Sons.