Big Data Analysis for Customer Purchase Behavior: Challenges and Opportunities

Odeta Shtrepi

Master's thesis

Abstract:

The scale of data in the past decades has shifted the way people, businesses and governments find value and make decisions. Nowadays data is the core and heart of every corporation and leveraging the analysis of it is of primary importance.This master thesis provides a literature review of the most common and statistical challenges of Big Data as well as an overview of the most used statistical modeling and techniques for analyzing it. It also gives an overview of Customer Purchase Behavior Analysis that has been done previously. In the practical part, a dataset of Customer Purchase Behavior is used for descriptive analysis as well as predictive modeling. Some of the main predictive techniques are used to compare them with each other and to come to a conclusion on which of them is the best to use when dealing with customer purchase data.

Keywords

Big Data, Predictive Modeling, Descriptive Analytics, linear regression, ridge regression, decision tree, random forest, train set, test set

Jazyk práce: English

Datum vytvoření / odevzdání či podání práce: 29. 3. 2019

Obhajoba závěrečné práce

• Vedúci: Ing. Tomáš Hlavsa, Ph.D.

Czech University of Life Sciences Prague

Faculty of Economics and Management

Master programme / odbor:
Systems Engineering and Informatics / Informatics