Computational Tools and IT for Analytics (BAN 835)

2021 Fall
Sabancı Business School
Business Analytics(BAN)
3
10
Altuğ Tanaltay atanaltay@sabanciuniv.edu,
Click here to view.
English
Doctoral, Master
--
Click here to view.

CONTENT

This course explores both the functional and technical environment for the creation, storage, and use of the most prevalent source and type of data for business analysis. Students will learn how to access and leverage information via SQL for analysis, aggregation to visualization, MapReduce, Apache Spark and Graph databases. This course will also give an introduction to a set of tools and techniques for dealing with large data such as Python and R.

LEARNING OUTCOMES

PROGRAMME OUTCOMES


1. Develop the ability to use critical, analytical, and reflective thinking and reasoning 5

2. Reflect on social and ethical responsibilities in his/her professional life. 2

3. Gain experience and confidence in the dissemination of project/research outputs 1

4. Work responsibly and creatively as an individual or as a member or leader of a team and in multidisciplinary environments. 1

5. Communicate effectively by oral, written, graphical and technological means and have competency in English. 5

6. Independently reach and acquire information, and develop appreciation of the need for continuously learning and updating. 5


1. Develop, interpret and use statistical analyses in decision making. 5


1. Demonstrated understanding of data-driven decision modeling and analysis concepts/frameworks. 5

2. Knowledge of and hands-on experience with fundamentals of business analytics, management information systems, statistical and prediction models. 5

3. Ability to transform complex data into valuable insight and resulting value-adding actions. 5

4. Skills in hands-on data-mining tools and techniques. 5

5. Exposure to the analytical methods in basic business disciplines such as marketing, operations, and finance 5