GRA 4142 Data Management and Python Programming
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.
- Understand basic concepts of Python programming.
- To gain basic knowledge in data analysis.
- 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
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.
- 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.
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.
Open-source software (will be specified during the first session).
The sessions will be organized as a mixture of lectures and working on in-class assignments.
In addition to the organized classes students are expected to prepare for the sessions by watching selected videos online and/or reading selected texts. Students are also expected to work on (ungraded) assignments after each session, either individually or in small groups (of 2-3 students). More information will be given during the first session.
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.
The exam for this course has been changed. The course now has one exam instead of two. It is not possible to retake one of the old exam versions. If you want to improve your grade in the course you will have to retake the new 100% exam. The code for the new exam is GRA 41423.
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 spesific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.
Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.
|Exam category||Weight||Invigilation||Duration||Grouping||Comment exam|
Form of assessment:
Internal and external examiner
Examination when next scheduled course
|Form of assessment:||Written submission|
|Exam code:||GRA 41423|
|Resit:||Examination when next scheduled course|
Group work / Assignments
Prepare for teaching
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.