Data Processing and Visualisation 2400-ZEWW182
Classes are conducted remotely via the Zoom platform. They include writing code in SAS 4GL and SQL and using ready-made procedures and tools in SAS Viya. Classes may be recorded and shared on Google Drive. Students learn the process of transforming data into information and knowledge, focusing on processing, analysis, and visualization. These processes are fundamental for financial institutions and enterprises analyzing large datasets. No prior programming knowledge is required. Assessment: the final grade is the higher score from two forms: short ongoing exercises (100%) or a final project (100%), both via the e-learning platform.
The course is aimed at individuals with basic IT tool knowledge who have completed "Computer Science Fundamentals".
Program:
1. Data processing in SAS 4GL – syntax, libraries, main loop, PDV vector.
2. Reading data in various formats (Excel, Access, XML, Oracle).
3. Creating programs (DATA and PROC steps), saving data, ODS technology.
4. Data aggregation, group processing, conversion, and transposition.
5. Merging sets, formats/informats, sorting, and indexing.
6. SQL – basic queries, aggregation, calculated columns, nested queries.
7. SQL – joining tables, creating views, SQL in SAS Viya.
8. Procedures: MERGE, SET, IMPORT, EXPORT, CONTENTS, FORMAT, PRINT, PLOT, SORT, INFILE, INPUT, PUT, DATALINES.
9. Advanced procedures and instructions.
10. Aggregation procedures: FREQ, MEANS, UNIVARIATE.
11. Graphical visualization in SAS Viya.
12. Publishing results, multidimensional structures, reports, server programs, cooperation with MS Word/Excel.
13. Advanced reading/merging: observation references, concatenation.
14. Creating programs extending system functionality.
Szacunkowy nakład pracy studenta: 3ECTS x 25h = 75h
(K) - godziny kontaktowe (S) - godziny pracy samodzielnej
wykład (zajęcia): 15h (K) 0h (S)
ćwiczenia (zajęcia): 15h (K) 0h (S)
egzamin: 3h (K) 0h (S)
konsultacje: 7h (K) 0h (S)
przygotowanie do ćwiczeń: 0h (K) 5h (S)
przygotowanie do wykładów: 0h (K) 5h (S)
praca z materiałami dodatkowymi umieszczanymi na platformie Moodle : 0h (K) 10h (S)
przygotowanie do kolokwium: 0h (K) 15h (S)
przygotowanie do egzaminu: 0h (K) 0h (S)
Razem: 40h (K) + 35h (S) = 75h
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Term 2025Z:
None |
Course coordinators
Type of course
Prerequisites (description)
Learning outcomes
KNOWLEDGE:
The student knows data processing, analysis, and visualization methods; knows database processing, merging, aggregation, and transposition techniques; understands SAS 4GL constructs (variables, functions, loops, macros) and SQL basics.
SKILLS:
The student can create/modify datasets using SAS 4GL and SQL; design/implement programs for data processing; analyze code correctness, test, and debug; interpret SAS 4GL/SQL code and implement algorithms.
SOCIAL COMPETENCES:
The student understands the role of data processing in organizations; identifies economic benefits; values SAS 4GL/SQL as efficiency tools; is aware of the need for continuous self-development in IT.
Assessment criteria
Based on the higher result of: ongoing short exercises (100%) or a final project (100%) via https://elearning.wne.uw.edu.pl/.
Grading scale:
[50, 60) - 3;
[60, 70) - 3.5;
[70, 80) - 4;
[80, 90] - 4.5;
(90, 100] - 5.
Bibliography
1. Painless Windows: A Handbook for SAS Users, Third Edition, Jodie Gilmore
2. The Little SAS Book: A Primer, Third Edition, Lora D. Delwiche, Susan J. Slaughter
3. SAS Programming by Example, Ron Cody, Ray Pass
4. SAS Functions by Example, Ron Cody
5. SAS Certification Prep Guide: Base Programming SAS
6. https://support.sas.com/en/knowledge-base.html
7. SAS OnLineDoc
Supporting materials for classes published on the e-learning platform https://elearning.wne.uw.edu.pl/
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Term 2025Z:
None |