Inclusion Of Data Science For The Administration Of Data Lakes, Data Analytics And Visualization For Big Data Applications And Services
Keywords:
Advertisement Marketing, Big Data Analytics, Digital TransformationAbstract
The research set out to assess how analytics applied to large amounts of data may help revolutionize the global economy. Consultants versed in marketing transformation and the use of big data served as the sample for this research. A total of 396 consultants were invited to take part in the research by receiving the online survey questionnaire; however, only 118 actually got around to starting the survey. The fact that barely half of businesses generate business events and just a quarter of businesses assess critical performance metrics like profitability demonstrates the necessity for such information. It raises the question of whether or not this category is in high demand. The genuine effect is more significant than whether the change is radical or revolutionary, at least from a pragmatic point of view. In addition, recent research indicates that enterprises can provide exact customer support using the new interface, which is consistent with the expected growth in post-purchase boost. Given the prevalence of these shifts, the results are not surprising. Because of the proliferation of mobile and social apps, consumers now have more options than ever before for gathering the information they need to make educated purchasing decisions. This research reveals that both institutions and consumers have higher expectations for the use of automation and self-service communication. The findings confirmed the importance of such feedback in providing a foundation for companies to validate their concerns.
Downloads
References
Márquez, A. C., & Ruiz Usano, R., Global production: a handbook for strategy and implementation, edited by E. Abele, T. Meyer, U. Näher, G. Strube and R. Sykes (2009).
Niebel, T., Rasel, F., & Viete, S.,BIG data–BIG gains? Understanding the link between big data analytics and innovation. Economics of Innovation and New Technology, Volume 28, Issue 3, 296-316 (2019).
Shabbir, J., & Anwer, T., Artificial Intelligence and its Role in Near Future,Volume 14, Issue (8), 1–11. Retrieved from http://arxiv.org/abs/1804.01396 (2018).
Scoble, R., Israel, S. & Benioff, M. R., Age of context: Mobile, sensors, data and the future of privacy, US: Patrick Brewster Press 1st edition (2014).
Lindstrom, M.,Small Data. Plassen Verlag, ein Imprint der Börsenmedien AG (2016). Available at: https://www.perlego.com/book/1045576/small-data-pdf (Accessed: 25 September 2021).
Larrey. P., Connected World: From Automated Work to Virtual Wars: The Future, By Those Who Are Shaping It.
Publisher Penguin UK. Published on Mar 2, (2017). Pages 320. ISBN 9780241981191
De Luca, L. M., Herhausen, D., Troilo, G., & Rossi, A. How and when do big data investments pay off? The role of marketing affordances and service innovation. Journal of the Academy of Marketing Science, Volume 49, Issue (4), 790-810 (2021).
Bendle, N. T., & Wang, X. S., Uncovering the message from the mess of big data. Business Horizons, Volume 59, Issue (1), 115-124 (2016).
Moro, S., Rita, P., & Vala, B., Predicting social media performance metrics and evaluation of the impact on brand building: A data mining approach. Journal of Business Research, Volume 69, Issue (9), 3341-3351 (2016).
Erevelles, S., Fukawa, N., & Swayne, L., Big Data consumer analytics and the transformation of marketing. Journal of business research, Volume 6, Issue (2), 897-904 (2016).
Miklosik, A., & Evans, N., Impact of big data and machine learning on digital transformation in marketing: A literature review. Ieee Access, 8, 101284-101292 (2020).
Pappas, I. O., Mikalef, P., Giannakos, M. N., Krogstie, J., & Lekakos, G., Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies. Information Systems and e- Business Management, Volume 16, Issue (3), 479-491(2018).
Schwertner, K., Digital transformation of business. Trakia Journal of Sciences, Volume 15 , Suppl. 1, (1), 388-393 (2017).
Jabbar, A., Akhtar, P., & Dani, S., Real-time big data processing for instantaneous marketing decisions: A problematization approach. Industrial Marketing Management, Volume 90, 558-569 (2020).
Wang, J., Zhang, W., & Yuan, S., Display advertising with real-time bidding (RTB) and behavioural targeting. Foundations and Trends® in Information Retrieval, 11(4-5), 297-435 (2017).
Sarker, Md., Wu, M.,Hossin, Md., Smart governance through bigdata: Digital transformation of public agencies. 2018 International Conference on Artificial Intelligence and Big Data (ICAIBD). IEEE, INSPEC Accession Number: 17894265. DOI: 10.1109/ICAIBD. 8396168 (2018).
Liu, J., Li, T., Xie, P., Du, S., Teng, F., Yang, X., Urban big data fusion based on deep learning: An overview. Information Fusion, Volume 53, Pages 123-133 (2020).
Mawed, M., & Aal-Hajj, A., Using big data to improve the performance management: A case study from the UAE FM industry. Facilities, Volume 35, pages (13–14, SI), 746–765 (2017).
Khan, Z., & Vorley, T., Big data text analytics: An enabler of knowledge management. Journal of Knowledge Management (2017).
Johnson, D. S., Muzellec, L., Sihi, D., & Zahay, D., The marketing organization’s journey to become data-driven. Journal Of Research In Interactive Marketing, Volume 13, Issue (2), 162–178 (2019). https://doi.org/10.1108/JRIM12-2018-0157
O’Neill, E., 10 companies that are using big data. Retrieved from: https://www.icas.com/insight/technology/10- companies-using-big-data (2016).
Zeng, J., & Glaister, K. W. Value creation from big data: Looking inside the black box. Strategic Organization,
Volume 16, Issue (2), 105–140 (2018). https://doi.org/10.1177/1476127017697510
Talón-Ballestero, P., González-Serrano. L., Soguero-Ruiz, C., Muñoz-Romerob, S., Rojo-Álvarez. L., Using big data from Customer Relationship Management information systems to determine the client profile in the hotel sector. Tourism Management Volume 68, October, Pages 187-197 (2018).
Kostakis, P., & Kargas, A., Big-Data Management: A Driver for Digital Transformation? Information, 12(10), 411 (2021).
Lucas, H., Agarwal, R., El Sawy, O., Weber, B., "Impactful Research on Transformational Information Technology: An Opportunity to Inform New Audiences," MIS Quarterly, (37: 2) pp.371-382 (2013).
Kothari. C. R., Research Methodology: Methods and Techniques. New Age International, Analysis of covariance - 401 pages (2004).
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M., A primer on partial least squares structural equation modeling (PLS-SEM): Sage Publications (2016).
Granados, N., & Gupta, A., Transparency strategy: Competing with information in a digital world. MIS Quarterly: Management Information Systems, Volume 37, Issue (2), 637-641 (2013).
Cao, L., & Li, L., "The Impact of Cross-Channel Integration on Retailers’ Sales Growth." Journal of Retailing 91.2 , 198-216 (2015).
Hennig-Thurau, T., Malthouse, E., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., Skiera, B., The Impact of New Media on Customer Relationships. Journal of Service Research, Volume 13, Issue (3) 311-330 (2010). sagepub.com/journalsPermissions.nav DOI: 10.1177/1094670510375460 http://jsr.sagepub.com
Huang, Jimmy C., Henfridsson, Ola, Liu, Martin J. and Newell, Susan., Growing on steroids : rapidly scaling the user base of digital ventures through digital innovation. MIS Quarterly, Volume 41, Issue (1) (2017).
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Ravi Kumar, Talib Ahmad, Shahid Ahmad, Niraj Kumar
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.