Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Business Intelligence Laboratory 

    A tantárgy neve magyarul / Name of the subject in Hungarian: Üzleti intelligencia labor

    Last updated: 2024. február 21.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics     		MSc, Applied Informatics Main specialization
    Course ID Semester Assessment Credit Tantárgyfélév
    VIAUMB09   0/0/3/f 5  
    3. Course coordinator and department Dr. Ekler Péter,
    Web page of the course https://www.aut.bme.hu/Course/VIAUMB00
    4. Instructors

    Dr. Péter Ekler

    Associate Professor

    Automation and Applied Informatics

    Sik Dávid

    		Assistant ProfessorAutomation and Applied Informatics

    Pomázi Krisztián

    Assistant Professor

    Automation and Applied Informatics

    Békési Gergő Bendegűz

    PhD Student

    		Automation and Applied Informatics

    5. Required knowledge Database management, web technolgies, object oriented programming
    6. Pre-requisites
    Kötelező:
    NEM
    (TárgyEredmény( "BMEVIAUMB00", "jegy" , _ ) >= 2
    VAGY
    TárgyEredmény("BMEVIAUMB00", "FELVETEL", AktualisFelev()) > 0)

    A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

    A kötelező előtanulmányi rend az adott szak honlapján és képzési programjában található.

    Ajánlott:
    Mandatory: EN BMEVIAUMA24 Business Intelligence 
    7. Objectives, learning outcomes and obtained knowledge Practice the materials of Business Intelligence Subject.
    8. Synopsis
    The course will consist of 4 computer labs (4x45p) (one independent) at the beginning of the semester and one (independent) project assignment

    - The topics of the labs are as follows:
       - Using open source BI tools, data loading, reporting
       - ELK based development  
       - MSSQL based business intelligence solution development, PowerBI in practice
       - Data analysis, use of statistical and data mining tools

    Attendance at labs will be monitored by the lab leader.

     
    Consultation on the project assignment will be provided at least 1 time during the semester by prior arrangement, the lab leader can be contacted separately with specific questions.

    The project assignment must be presented to the lab leader at the end of the semester at a fixed time.

    Topic of the project assignment: development of your own BI solution: connecting data source(s), building ETL processes, displaying and calculating reports and decision KPIs
    9. Method of instruction Laboratory work and home project
    10. Assessment
    During term time:

    - Attendance at timetabled classes,
     

    - Successful completion of laboratory exercises. Students who are not sufficiently prepared will not be allowed to participate in the laboratory exercise and will have to make up for it. An additional condition is the successful completion of the laboratory and the acceptance of the report documenting this by the instructor in charge of the measurement. The document of the lab work must be completed by the end of the 2nd week of the lab.


    - Achieve a minimum score of 40% by completing the project assignment.

    - The mid-semester grade will consist of a 50-50% split of the lab protocol grade and the project assignment score.
    11. Recaps One laboratory work can be made up during the semester.
    12. Consultations As agreed with the professors.
    13. References, textbooks and resources

    Morgan Kaufmann, Business Intelligence Guidebook: From Data Integration to Analytics, 2014.

    Joshua N. Milligan, Learning Tableau 10 - Second Edition: Business Intelligence and data visualization that brings your business into focus, 2016.

    Alex Holmes: Hadoop in Practice, Second Edition, 2014.

    John Russel: Cloudera Impala, 2013.

    Phil Simon: Too Big to Ignore: The Business Case for Big Data, 2013.

    Stephen Few: Information Dashboard Design: Displaying Data for At-a-Glance Monitoring, 2013.

    Ralph Kimball, Margy Ross, Warren Thornthwaite, Joy Mundy, Bob Becker: The Kimball Group Reader: Relentlessly Practical Tools for Data Warehousing and Business Intelligence, 2010.

    Howard Dresner: The Performance Management Revolution: Business Results Through Insight and Action, 2007.
    14. Required learning hours and assignment
    Laboratories42
    Prepare for laboratories38
    MidTerm test0
    Homework70
    Written material0
    Exam0
    Sum150