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Π.Μ.Σ στη «Χρηματοοικονομική Τεχνολογία (FinTech)»

M.Sc. in Financial Technology (FinTech)

Databases for Business Analytics

3rd Semester, Course Code: ΜΕΧΤΕ303

Credits: 7,5

Learning Outcomes

Upon successful completion of the course, the student:

(a) will be able to draw Entity-Relationship diagrams to illustrate the structure and characteristics of a relational database.

(b) will have the ability to manage relational databases through Azure SQL, specifically: (i) create objects, (ii) fill in tables, (iii) update existing data, and (iv) execute queries on databases.

(c) 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.

(d) will be able to use econometric methods to focus on the analysis of a business in order to make optimal decisions.

General Competences

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:

(a) search for, analysis and synthesis of data and information, with the use of the necessary technologies,

(b) decision-making

(c) working independently

(d) production of free, creative and inductive thinking

(e) criticism and self-criticism

Course Content

Lectures:

  1. Descriptive Analytics: Probability Theory, Frequency distributions, Hypothesis testing, Statistical inference.
  2. Diagnostic Analytics: Regression models, Time-series analysis.
  3. Forecasting analytics: Objective and Subjective Probability, Bayes Rule, Decision making under uncertainty, Monte Carlo Simulations.

Laboratory Practice:

  • Entity Relationship diagrams.
  • Structure of relational databases
  • Basic commands in Azure SQL: (i) objects creation, (ii) tables storing, (iii) updating of existing data, and (iv) execution of queries on databases.
  • Basic command in R: (i) connection with Azure SQL, (ii) accessing and processing of data, (iii) application of econometric methods to analyze data.
  • Empirical applications.

Student Performance Evaluation

Formative and summative assessment is carried out. The final evaluation of the students is done by a written exam or an oral exam. It is based on problem solving, short answer questions and development questions.

Bibliography

Suggested Bibliography

1) Lecture Notes

2) Lecture Slides

Related Academic Journals