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Vol. 1 No. 1 (2022): International Transactions on Artificial Intelligence

Issue Published : November 30, 2022
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The Digital Economy's Use of Big Data

https://doi.org/10.34306/italic.v1i1.167
Mochamad Wahyudi
University of Bina Sarana Informatika
Vivi Meilinda
University of Muhammadiyah Kuningan College of Health Sciences
Alfiah Khoirunisa
University of Raharja

Corresponding Author(s) : Mochamad Wahyudi

[email protected]

International Transactions on Artificial Intelligence, Vol. 1 No. 1 (2022): International Transactions on Artificial Intelligence
Article Published : November 27, 2022

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Abstract

The function of Big Data technology and Data Science in the contemporary digital economy is examined in this article. According to the author, large and medium-sized businesses in the retail and service sectors have a greater interest in utilizing them. Banks, mobile operators, and major manufacturing firms actively employ these technologies (Artificial Intelligence) to evaluate data on equipment failures and minimize downtime, which enables cost-reduction. Big Data technology serves as a liquid product and a prerequisite for boosting business profitability through individualized customer care and predictive analytics. It is crucial to ensure the formation of unique data exchanges and legalize a single definition of big data for the modern digital economy.

Keywords

Big Data technology Data Science Digital Economy Digital Transformation Artificial Intelligence

Full Article

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References
  1. Gobareva, Y. L., Gorodetskaya, O. Yu., & Kochanova, E. R. (2015). Features of Big Data technology to improve the quality of operation of CRM-systems. Transport business in Russia, 5, 62-63.
  2. Baburin, V. A., & Janenko, M. E. (2014). Big Data technologies in service: new markets, opportunities
  3. and challenges. Technical and technological problems of service,1(27), 100-105.
  4. Maltseva, S. V., & Lazarev, V. V. (2015). Big Data E- Marketing Marketing Analytics. Information Technologies in Design and Production, 21, 62–67.
  5. Suleikin, A. S. (2015). Possibilities of using Big Datatechnology in large retail. European Research, 10(11),77-79.
  6. Munoz, M. (2013, November). Space systems modeling using the Architecture Analysis & Design Language (AADL). In 2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) (pp. 97-98). IEEE.
  7. Herodotou, H., Lim, H., Luo, G., Borisov, N., Dong, L., Cetin, F. B., & Babu, S. (2011). Starfish: A Self-tuning System for Big Data Analytics. CIDR. Fifth Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, 11, 261–272.
  8. Michalik, P., Štofa, J., & Zolotova, I. (2014, January). Concept definition for Big Data architecture in the
  9. education system. In 2014 IEEE 12th International Symposium on Applied Machine Intelligence and
  10. Informatics (SAMI) (pp. 331-334). IEEE.
  11. Bulgakov, A. (2017). Big Data в финансах (Big Data in Finance). Journal of Corporate FinancenResearch, 11(1), 7-15.
  12. Saltz, J. S., & Grady, N. W. (2017, December). The ambiguity of data science team roles and the need for
  13. a data science workforce framework. In 2017 IEEE International Conference on Big Data (Big Data)
  14. (pp.2355-2361). IEEE.
  15. Avdeeva, I. L., Polyanin, A. V., & Golovina, T. A. (2019). Digitalization of industrial economic systems:
  16. problems and consequences of modern technologies. Economy. Control. Law, 19(3), 238-245.
  17. Hu, V. V., & Kaabouch, N. (2014). Big Data Management, Technologies, and Applications. Hershey: IGI Global.
  18. Ivashchenko, A. V., & Dvoinina, O. V. (2014). Analysis of super-large data arrays (Big Data) in
  19. a single information space of a research and production enterprise. Science and World, 12(16), 44-47.
  20. Ia, T. V. (2014). Natural and artificial information field. Mezhdunarodnyi zhurnal prikladnykh
  21. i fundamental'nykh issledovanii-International journal of applied and fundamental research, 5(2), 178-180.
  22. Bayliss, D. (2016). Models for Big Data. In Big Data Technologies and Applications (pp. 237-255).
  23. Springer, Cham.
  24. Golov, N. I., & Kravchenko, T. K. (2014). Designing a data warehouse to solve Big Data problems.
  25. Information Technology in Design and Production, 1(153), 56-61.
  26. Jacobs, A. (2009). The pathologies of big data. Queue, 7(6), 10-19.
  27. Tsvetkov, V. Y. (2014). Worldview Model as the Result of Education. World Applied Sciences Journal, 31(2), 211-215.
  28. Chernyak, L. (2011). Big data: a new theory and practice. Open systems. SUBD, 10.
  29. Denisov, L. V., Boitsov, A. G., & Siluyanova, M. V. (2018). Surface Hardening in Hydraulic Cylinders for
  30. Airplane Engines. Russian Engineering Research, 38(12), 1080-1083.
  31. Sorokin, A. E., Bulychev, S. N., Novikov, S. V., & Gorbachev, S. I. (2019). Information Science in
  32. Occupational Safety Management. Russian Engineering Research, 39(4), 324-329.
  33. Chekharin, E. E. (2016). Big data: big problems. Prospects for Science and Education, 3(21), 7-11.
  34. Rahardja, U., Lutfiani, N., & Amelia, S. (2019). Creative Content Marketing In Scientific Publication Management In Industrial Era 4.0. APTISI Transactions on Management (ATM), 3(2), 168–177.
Read More

References


Gobareva, Y. L., Gorodetskaya, O. Yu., & Kochanova, E. R. (2015). Features of Big Data technology to improve the quality of operation of CRM-systems. Transport business in Russia, 5, 62-63.

Baburin, V. A., & Janenko, M. E. (2014). Big Data technologies in service: new markets, opportunities

and challenges. Technical and technological problems of service,1(27), 100-105.

Maltseva, S. V., & Lazarev, V. V. (2015). Big Data E- Marketing Marketing Analytics. Information Technologies in Design and Production, 21, 62–67.

Suleikin, A. S. (2015). Possibilities of using Big Datatechnology in large retail. European Research, 10(11),77-79.

Munoz, M. (2013, November). Space systems modeling using the Architecture Analysis & Design Language (AADL). In 2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) (pp. 97-98). IEEE.

Herodotou, H., Lim, H., Luo, G., Borisov, N., Dong, L., Cetin, F. B., & Babu, S. (2011). Starfish: A Self-tuning System for Big Data Analytics. CIDR. Fifth Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, 11, 261–272.

Michalik, P., Štofa, J., & Zolotova, I. (2014, January). Concept definition for Big Data architecture in the

education system. In 2014 IEEE 12th International Symposium on Applied Machine Intelligence and

Informatics (SAMI) (pp. 331-334). IEEE.

Bulgakov, A. (2017). Big Data в финансах (Big Data in Finance). Journal of Corporate FinancenResearch, 11(1), 7-15.

Saltz, J. S., & Grady, N. W. (2017, December). The ambiguity of data science team roles and the need for

a data science workforce framework. In 2017 IEEE International Conference on Big Data (Big Data)

(pp.2355-2361). IEEE.

Avdeeva, I. L., Polyanin, A. V., & Golovina, T. A. (2019). Digitalization of industrial economic systems:

problems and consequences of modern technologies. Economy. Control. Law, 19(3), 238-245.

Hu, V. V., & Kaabouch, N. (2014). Big Data Management, Technologies, and Applications. Hershey: IGI Global.

Ivashchenko, A. V., & Dvoinina, O. V. (2014). Analysis of super-large data arrays (Big Data) in

a single information space of a research and production enterprise. Science and World, 12(16), 44-47.

Ia, T. V. (2014). Natural and artificial information field. Mezhdunarodnyi zhurnal prikladnykh

i fundamental'nykh issledovanii-International journal of applied and fundamental research, 5(2), 178-180.

Bayliss, D. (2016). Models for Big Data. In Big Data Technologies and Applications (pp. 237-255).

Springer, Cham.

Golov, N. I., & Kravchenko, T. K. (2014). Designing a data warehouse to solve Big Data problems.

Information Technology in Design and Production, 1(153), 56-61.

Jacobs, A. (2009). The pathologies of big data. Queue, 7(6), 10-19.

Tsvetkov, V. Y. (2014). Worldview Model as the Result of Education. World Applied Sciences Journal, 31(2), 211-215.

Chernyak, L. (2011). Big data: a new theory and practice. Open systems. SUBD, 10.

Denisov, L. V., Boitsov, A. G., & Siluyanova, M. V. (2018). Surface Hardening in Hydraulic Cylinders for

Airplane Engines. Russian Engineering Research, 38(12), 1080-1083.

Sorokin, A. E., Bulychev, S. N., Novikov, S. V., & Gorbachev, S. I. (2019). Information Science in

Occupational Safety Management. Russian Engineering Research, 39(4), 324-329.

Chekharin, E. E. (2016). Big data: big problems. Prospects for Science and Education, 3(21), 7-11.

Rahardja, U., Lutfiani, N., & Amelia, S. (2019). Creative Content Marketing In Scientific Publication Management In Industrial Era 4.0. APTISI Transactions on Management (ATM), 3(2), 168–177.

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