Proceedings of the International Conference on Digital Technologies in Logistics and Infrastructure (ICDTLI 2019)

Analysis of business intelligence tools and development of solutions for marketing activities

Authors
Anton P. Shaban, Zilia U. Bikkulova, Anastasiy I. Klimin, Roman S. Marchenko
Corresponding Author
Anton P. Shaban
Available Online September 2019.
DOI
https://doi.org/10.2991/icdtli-19.2019.51How to use a DOI?
Keywords
marketing, big data, business intelligence
Abstract
The objective of the research is the analysis of business intelligence tools and development of solutions for mar-keting activities based on business intelligence tools. In the framework of the current research, following methods have been used: analysis and modeling. Text sources were analyzed in order to describe and classify use cases of big data in market-ing activities and to describe and classify big data and business intelligence tools and technologies in marketing. As the result of the research, a big data classifier for marketing activity was de-veloped and possible solutions for marketing activity analytics were studied and proposed. The classifier can be considered a new result of the study, since there was no classification of big data in marketing activities so far. The current research can be used to help organization of BI analytics in marketing activities. However it is necessary to consider actualization of data on ex-isting tools and technologies.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Anton P. Shaban
AU  - Zilia U. Bikkulova
AU  - Anastasiy I. Klimin
AU  - Roman S. Marchenko
PY  - 2019/09
DA  - 2019/09
TI  - Analysis of business intelligence tools and development of solutions for marketing activities
BT  - Proceedings of the International Conference on Digital Technologies in Logistics and Infrastructure (ICDTLI 2019)
PB  - Atlantis Press
SP  - 286
EP  - 291
SN  - 2589-4900
UR  - https://doi.org/10.2991/icdtli-19.2019.51
DO  - https://doi.org/10.2991/icdtli-19.2019.51
ID  - Shaban2019/09
ER  -