Models for Decision Support Systems

Sheikh Samsuzzhan Alam, MS

Diplomová práce

Abstract:

Enterprises deals with a highly dynamic environment that requires management to integrate available knowledge gained from the data and information for effective decision-making. The advancement of the web technology and cloud services make it possible to integrate the whole process. As a result, all most all of the computing work and analytics is delegated to the computer and the underlying systems. Improvement of Internet technologies and software systems provide a new means of decision support functionalities and delivering decision support within a very short time frame. As large enterprises generates high volume of internal and external data some Data Mining technique is also need to build a proper data and model driven Decision Support System (DSS) application. The process of Data Mining converts information to knowledge by using tools from the disciplines of computational statistics, database technologies, machine learning, signal processing, nonlinear dynamics, process modeling, simulation, and allied disciplines. Data Mining allows business problems to be analyzed from diverse perspectives, including dimensionality reduction, correlation and co-occurrence, clustering and classification, regression and forecasting, anomaly detection, and change analysis. The tools that enable the transformation of raw data to actionable predictive insights are collectively referred to as decision support tools. This paper describes process of building a Data Mining based Decision Support System from scratch for enterprise decision making purpose Which offers basic descriptive analytics and advance predictive modeling as well. Through our study we were able to analyse the clothing retailing industry for a particular company expansion in Australia which is currently running operation in New South Wales. We user several different technology such as Alteryx Designer and R Language for data preparation and advance modeling of available data. For visualization Tableau Desktop and Tableau Server to create a interactive decision support application.

Keywords

Decisions Support System, Data Mining, ime Series Forecasting, Tableau

Jazyk práce: angličtina

Datum vytvoření / odevzdání či podání práce: 9. 5. 2017

Obhajoba závěrečné práce

• Vedoucí: doc. RNDr. Helena Brožová, CSc.
• Oponent: Martin Flégl, Ph.D.

Česká zemědělská univerzita v Praze

Provozně ekonomická fakulta

Magisterský studijní program / obor:
Systems Engineering and Informatics / Informatics