Business intelligence laboratory (ENVIAUMB00)

Tárgy hivatalos adatlapja: https://portal.vik.bme.hu/kepzes/targyak/VIAUMB00/en

Requirements

  • The course has 7 laboratories. See the schedule below.
  • Most laboratories will require you to work individually on the assignments.
  • You must prepare for the laboratories. Use the laboratory exercises and related material listed below, and also review what you have learned about the specific topic before.
  • During the laboratories you must complete the exercises, and hand in the solutions, as well as any related material, as requested by the teacher.
  • Completing a laboratory requires you to arrive on time, be present during the class, and submit the solutions at the end of the lab, or by the end of the week.
    • The laboratories begin at 8.15. If you are late, you disturb the class, the instructor, and you peers. Therefore, arriving late to the laboratories is sanctioned by considering you absent.
    • Please refer to the attendance requirements as specified by the BME code of studies; see Title 67.
    • Exceptions are laboratories "MSSQL" and "Elasticsearch". These laboratories are completed as homework, and optional consulation is offered during the class (thus no attendace requirement).
  • Your solutions will be graded.
  • If you are not present at a laboratory, you cannot submit your solution - except for laboratories "MSSQL" and "Elasticsearch".


Final grade

  • If absence from the total number of practical and laboratory practice lessons ex-ceeds thirty per cent, the credits for the subject cannot be obtained. See the BME code of studies; see Title 68.
  • The final grade is the averge grade of laboratories. (Non-completed laboratory is calculated with grade 1.)
 
Accessing the exercises and other course material
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Scheduling and laboratory location

Week Date  Tuesday 08.15-12.00
    topic location teacher
1 2020.02.11 no class    
2 2020.02.18 no class    
3 2020.02.25 NoSQL   Sik Dávid
4 2020.03.03 BPMN   Kövesdán Gábor
5 2020.03.10 Pandas + Jupíter   Kovács Ádám / Ács Judit
6 2020.03.17 Data visualization   Jánoky László
7 2020.03.24 Pentaho   Jánoky László
8 2020.03.31 MSSQL homework Dudás Ákos
9 2020.04.07 Elasticsearch homework Dudás Ákos

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