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

The goal of the course is to practice the material learned during Data-driven systems through laboratory exercises.

-        Microsoft SQL Server programming (platform dependent SQL queries, triggers, cursors, stored procedures)

-        MongoDB database platform programming (data access methods, client-side data access using C# language, atomic data modifications, aggregation pipelines)

-        Query optimization, usage of indices (CI, NCI, TS, CISC, CISE, NCISE, NSISC, NLJ algorithms comparison, performance evaluation)

-        Programming Entity Framework (Entity Data Model, query language)

-        SQL Reporting Services (basics of Reporting Services, data sources, datasets, tables, reports, formatting, diagrams)

-        Developing multi-tier applications using REST (REST-based service development in C# using Visual Studio)

Exercises are to be solved during a computer laboratory class. The classes focus mainly on individual work. The exercises define a framework in which the tasks should be completed (such as, starter source code). The solutions must be submitted electronically. The solutions are software source codes and/or documentation, which the exercises clearly define.

The laboratories can be of two type.

• Standard computer laboratory class with a handout and aids describing the exercises. The students mainly work alone, but there is an instructor available for questions. This type of laboratory is used for the topics and technologies where the presence of a laboratory instructor is important.

• Certain topics are suitable for completion and submission from at home. For these, the assigned time slot of the course is used for consultation option. Attendance of the consultation may require preliminary registration so that the required number of instructors can be provided. The following topics are available for this type of laboratory:

o   MongoDB database platform programming

o   Programming Entity Framework

a. During the semester:

- The student must prepare for the laboratories based on the materials of the exercises and the related materials of course Data-driven systems.

- For laboratories that require attendance, the student must arrive to the laboratory class on time and must participate in the laboratory class as the instructor and the exercise handout specifies it.

- For the laboratories that do not require attendance, the requirement is the completion of the exercises based on the laboratory handouts. During the completion of these laboratories, to ensure that the student did the work herself, the instructor may specify additional requirements that prove this fact. Such requirement can be, for example, the documentation of the work process through computer screenshots; frequent commits to a Git repository showing the incremental work process; or similar techniques. If the submission of the student does not adhere to these requirements, the instructor can require the student to participate in an additional class, where attendance is required, and the student must complete exercises similar to the work at home, but this time, supervised by instructors in person.

- Any material produced during the laboratory (including source code, documentation, etc., as specified by the instructor) shall be submitted to the instructor as requested. The exact deadline of submission can be specified by the instructor.

- Each laboratory is graded separately. The final grade is the average of the individual grades. Any laboratory that was not completed is counted with grade 1.  

b. During the exam period:

 None.

The laboratory classes where attendance is required may be repeated upon preliminary request, depending on room capacity. Materials not submitted until the deadline may not be handed in late.

Available upon request to the laboratory instructor.

Course materials and exercises.