Asia Pacific University Library catalogue


SALES PREDICTION AND BUSINESS DECISION MAKING / (Record no. 383326)

000 -LEADER
fixed length control field 02555nam a2200229 4500
003 - CONTROL NUMBER IDENTIFIER
control field APU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230625191246.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190127b2017 xxu||||| |||| 00| 0 eng d
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number PM-31-89
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name AUNG PYAE (TP052143)
9 (RLIN) 41581
245 10 - TITLE STATEMENT
Title SALES PREDICTION AND BUSINESS DECISION MAKING /
Statement of responsibility, etc AUNG PYAE.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Kuala Lumpur :
Name of publisher, distributor, etc Asia Pacific University,
Date of publication, distribution, etc 2019.
300 ## - PHYSICAL DESCRIPTION
Extent xiii, 94 pages :
Other physical details illustrations ;
Dimensions 30 cm.
502 ## - DISSERTATION NOTE
Dissertation note A thesis submitted in fulfillment of the requirements for the award of the degree of MSc. in Data Science & Business Analytics (UCMF1808DSBA)
520 ## - SUMMARY, ETC.
Summary, etc The sales prediction performs an important role in every market process and the decision making for sales of products are important to follow the demand of consumers. This research focuses on the study of sales prediction and business decision making for e-commerce retail business with data science research approach. The main goal of research is to perform data science analysis on collected sales data with minimum predictor variables to create advance sales prediction model to forecast future sales performance and identify new business decisions depending on the predicted results and data analysis report. Applying business intelligence, statistical modelling and machine learning are proposed to create intelligent prediction and analytical solution of retail business and optimization methods are also applied to create business decisions. Business decisions are made depending on analysis result using mathematical programming methods to set profitable decisions which can minimize or maximize capital and control the stock with decision results. The research mainly depends on the quantitative study in which statistical modelling techniques are applied using different predictive models and results gained are also in quantitative form. The result of this research is solving additional sales problems in online retail environment using predictable machine learning, statistical data analysis, business intelligence and applied operational research. The case study, methodology and decision are made from point of data science and business analyst view.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Business intelligence.
9 (RLIN) 41582
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Predictive analytics.
9 (RLIN) 41583
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Marketing
General subdivision Decision making.
9 (RLIN) 41584
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Dr. Booma Poolan Marikannan
Relator term Supervisor.
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856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://cas.apiit.edu.my/cas/login?service=https://library.apu.edu.my/apres/
Link text Available in APres
Public note - Requires login to view full text.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Masters Theses
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Use restrictions Not for loan Collection code Home library Current library Shelving location Date acquired Full call number Barcode Date last seen Copy number Koha item type Public note
Not Withdrawn Available   Not Damaged Restricted access Not for loan Masters Theses APU Library APU Library Reference Collection 14/12/2020 PM-31-89 00018451 14/12/2020 1 Reference Available in APres