Databases for Business Analytics

5th or 7th Εξάμηνο

Ακαδημαϊκό Έτος 2025-26

Με Μια Ματιά

Κωδικός Μαθήματος

ΧΡΒΔΕΑ

Τύπος Μαθήματος

Specialised and Skills Development

Γλώσσα Διδασκαλίας

Greek

Το μάθημα προσφέρεται σε φοιτητές Erasmus;

Τρόπος Παράδοσης

Face to Face

Χρήση Τεχνολογιών Πληροφορίας και Επικοινωνιών

Each student will use the R programming language as well as the SQL relational database through his/her Personal Computer.

Αυτοτελείς Διδακτικές Δραστηριότητεσ

Τύπος

Lectures

Εβδομαδιαίες Ώρες

Μονάδες ECTS

7,5

Περιγράμματα Σπουδών

🇬🇷 Ελληνικά

🇬🇧 Αγγλικά

Συνδεσμοι

Αξιολόγηση Φοιτητών

Greek, 80% Final Exam and 20% Project presentation at class (optional)

Μαθησιακά Αποτελέσματα

Upon successful completion of the course, the student:

will be able to draw Entity-Relationship diagrams to illustrate the structure and characteristics of a relational database.
will have the ability to manage relational databases through SQL, specifically: (i) create objects, (ii) fill in tables, (iii) update existing data, and (iv) execute queries on databases.
will be familiar with the R language and know its basic functions, which are needed to be able to process data stored in a relational database.
will be able to use econometric methods to focus on the analysis of a business in order to make optimal decisions.

Γενικές Ικανότητες

Within the framework of the combined skills that the graduate will acquire with the following all the courses of the study program, the course of Databases and Business Analytics aims for the graduate to acquire abilities:

search for, analysis and synthesis of data and information, with the use of the necessary technologies,
decision-making
working independently
production of free, creative and inductive thinking
criticism and self-criticism

Περιεχόμενο Μαθήματος

Section 1: SQL & Relational Databases

What is a relational database and how it is structured
Understanding table schema: fields, data types, constraints
Creating and managing tables using CREATE, ALTER, DROP
Using basic SQL commands: SELECT, WHERE, ORDER BY, DISTINCT, LIMIT
Aggregate functions and grouping: GROUP BY, HAVING
Joining tables: INNER JOIN, LEFT JOIN, etc.
Subqueries: IN, EXISTS, ANY, ALL
Creating virtual tables (Views) for reporting
Practical use of SQL Server Management Studio (SSMS)

Section 2: Econometric Tools for Practical Applications

What is regression and how it is used in economic analysis
Estimation of simple and multiple linear regression
Assumption checks and interpretation of results (p-values, R², t-tests)
Problems and diagnostic tests:
1. Multicollinearity
2. Heteroskedasticity
3. Autocorrelation
Application of econometric models to financial datasets

Section 3: Data Analysis with R

Using RStudio for statistical and econometric analysis
Connecting R to SQL Server (via DBI and odbc)
Retrieving data from SQL tables directly into R
Data processing with dplyr: filter(), select(), mutate(), summarise()
Creating basic visualizations (histograms, line charts, scatterplots)
Estimating and interpreting regression models using lm()
Full pipeline for analysis using SQL and R:
From SQL → R → Analysis → Econometric conclusions