GRA 4142 Data Management and Python Programming

GRA 4142 Data Management and Python Programming

Course code: 
GRA 4142
Department: 
Economics
Credits: 
6
Course coordinator: 
Alfonso Irarrazabal
Product category: 
Master
Portfolio: 
MSc in Business Analytics
Semester: 
2019 Autumn
Active status: 
Active
Teaching language: 
English
Course type: 
One semester
Introduction

In the new economy data will be an ever more important aspect of business. Firms are slowly reacting to more data available on consumer behavior and markets in general. Competence in programming skills is essential to extract information and knowledge from data.

Advances in our capability to generate and collect information are pushing us toward a business world centered around data. Databases are currently at the heart of modern organizations. This course covers the basic concepts of data management, database systems, and the use of databases in business applications.

The goals of this course are twofold:
i) to introduce learners to the basics aspects of Python programming with a special focus on data analysis

ii) to provide adequate technical detail related to capturing, cleaning, and accessing data, while emphasizing the organizational and implementation issues relevant in an organization environment.

Learning outcomes - Knowledge

First part

  • Understand basic concepts of Python programming.
  • To gain basic knowledge in data analysis.

Second part

  • Understand the principles of good database design;
  • Gain an understanding of relational database management systems;
  • Develop an understanding of Structured Query Language (SQL);
  • Comprehend how database systems are used for strategic and operational decision making
Learning outcomes - Skills

In general, students will develop analytical and digital skills associated to programming and data management. 

For the first part of the course, students will

  • Learn basic building blocks of Python programming such as variables, data types, loops, conditionals, functions etc.
  • Learn basic skills for data analysis to handle, analyze and visualize data using the Pandas package.

 

  • Learn how to collect, manage and analyze data in with emphasis on applications relevant for international business.

For the second part, they will

  • Develop entity-relationship diagrams, relational schemas, and data dictionaries for a database depending on a set of business rules;
  • Write SQL statements for a variety of data definition and data manipulation scenarios;
  • Being able to design data architecture solutions for several application needs and evaluate existing commercial database management systems in terms of these needs.
  • Be able to interface Python programs with a database.

 

General Competence
  • To evaluate the veracity of several types of data and decide whether it is meaningful to the problem being analyzed.
  • To demonstrate abilities of analytical and critical thinking.
  • Privacy and confidentiality concerns that may emerge from the use of sensitive data.
  • Explore the value of data in relation to corporate social responsibility and sustainability goals.

 

Course content

The first part of the course introduces students to Python programming. Students will use the Python syntax to work with, among others, different data types, loops, and functions.

The second part of this course will teach students the principles of working with relational databases. They will learn the principles of good database design, as well as the practical aspects of retrieving data from such databases using SQL. Finally, they will know how to interface programs written in python with a database.

Teaching and learning activities

The course will be a combination of lectures and tutorials. 

 

 

Software tools
No specified computer-based tools are required.
Additional information

Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.

All parts of the assessment must be passed in order to get a grade in the course.

Qualifications

All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA 41421
Grading scale:
ECTS
Grading rules:
Internal and external examiner
Resit:
Examination when next scheduled course
50No72 Hour(s)Group/Individual (1 - 3)
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA 41422
Grading scale:
ECTS
Grading rules:
Internal and external examiner
Resit:
Examination when next scheduled course
50No72 Hour(s)Group/Individual (1 - 3)
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:50
Invigilation:No
Grouping (size):Group/Individual (1-3)
Duration:72 Hour(s)
Comment:
Exam code: GRA 41421
Grading scale:ECTS
Resit:Examination when next scheduled course
Exam category:Submission
Form of assessment:Written submission
Weight:50
Invigilation:No
Grouping (size):Group/Individual (1-3)
Duration:72 Hour(s)
Comment:
Exam code: GRA 41422
Grading scale:ECTS
Resit:Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100