Cite this DOI

Raj Kumar Gudivaka (2024). Big Data and Robotic Process Automation: Driving Digital Transformation in the Telecommunications Sector. *Journal of Science & Technology*, *09*(02), 52. https://doi.org/10.46243/jst.2024.v9.i2.pp52-71

@article{rajkumargudivaka2024data,
  author    = {Raj Kumar Gudivaka},
  title     = {{Big Data and Robotic Process Automation: Driving Digital Transformation in the Telecommunications Sector}},
  journal   = {Journal of Science \& Technology},
  year      = {2024},
  month     = {feb},
  volume    = {09},
  number    = {02},
  pages     = {52},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2024.v9.i2.pp52-71},
  url       = {https://doi.org/10.46243/jst.2024.v9.i2.pp52-71},
  language  = {en},
  abstract  = {The telecom industry is undergoing a change because to the combination of Big Data analytics and Robotic Process Automation (RPA), which boosts customer happiness, operational efficiency, and strategic decision-making. While big data analytics makes it possible to handle and analyse massive datasets in order to derive relevant insights, robotic process automation (RPA) automates repetitive operations, lowers error rates, and speeds up processes. This study highlights the combined influence of RPA and Big Data on the digital transformation of the telecoms industry by examining their synergistic interaction. Key obstacles are identified by the research, including the possibility of implementing RPA incorrectly, the significance of protecting data privacy, and the need for qualified staff to oversee these technologies. According to the study results, 65\% of participants are aware of the risks involved in implementing RPA and stress the importance of thorough configuration and preparation. Furthermore, as noted by 55\% of respondents, maintaining data privacy in multi-departmental settings can be challenging. The results highlight the potential for transformation that can arise from strategically aligning RPA with Big Data, but they also highlight the dangers that must be addressed in order to effectively leverage these technologies. For telecom businesses looking to maximise their use of RPA and Big Data to maintain their competitiveness in the quickly changing digital market, this paper offers insightful analysis and helpful suggestions.}
}

TY  - JOUR
TI  - Big Data and Robotic Process Automation: Driving Digital Transformation in the Telecommunications Sector
AU  - Raj Kumar Gudivaka
JO  - Journal of Science & Technology
PY  - 2024
DA  - 2024/02/24/
VL  - 09
IS  - 02
SP  - 52
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - The telecom industry is undergoing a change because to the combination of Big Data analytics and Robotic Process Automation (RPA), which boosts customer happiness, operational efficiency, and strategic decision-making. While big data analytics makes it possible to handle and analyse massive datasets in order to derive relevant insights, robotic process automation (RPA) automates repetitive operations, lowers error rates, and speeds up processes. This study highlights the combined influence of RPA and Big Data on the digital transformation of the telecoms industry by examining their synergistic interaction. Key obstacles are identified by the research, including the possibility of implementing RPA incorrectly, the significance of protecting data privacy, and the need for qualified staff to oversee these technologies. According to the study results, 65% of participants are aware of the risks involved in implementing RPA and stress the importance of thorough configuration and preparation. Furthermore, as noted by 55% of respondents, maintaining data privacy in multi-departmental settings can be challenging. The results highlight the potential for transformation that can arise from strategically aligning RPA with Big Data, but they also highlight the dangers that must be addressed in order to effectively leverage these technologies. For telecom businesses looking to maximise their use of RPA and Big Data to maintain their competitiveness in the quickly changing digital market, this paper offers insightful analysis and helpful suggestions.
DO  - 10.46243/jst.2024.v9.i2.pp52-71
UR  - https://doi.org/10.46243/jst.2024.v9.i2.pp52-71
ER  -

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    "URL": "https://doi.org/10.46243/jst.2024.v9.i2.pp52-71",
    "title": "Big Data and Robotic Process Automation: Driving Digital Transformation in the Telecommunications Sector",
    "source": "Smart Scholars DOI Registry",
    "container-title": "Journal of Science & Technology",
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    "publisher": "Longman Publishers",
    "language": "en",
    "abstract": "The telecom industry is undergoing a change because to the combination of Big Data analytics and Robotic Process Automation (RPA), which boosts customer happiness, operational efficiency, and strategic decision-making. While big data analytics makes it possible to handle and analyse massive datasets in order to derive relevant insights, robotic process automation (RPA) automates repetitive operations, lowers error rates, and speeds up processes. This study highlights the combined influence of RPA and Big Data on the digital transformation of the telecoms industry by examining their synergistic interaction. Key obstacles are identified by the research, including the possibility of implementing RPA incorrectly, the significance of protecting data privacy, and the need for qualified staff to oversee these technologies. According to the study results, 65% of participants are aware of the risks involved in implementing RPA and stress the importance of thorough configuration and preparation. Furthermore, as noted by 55% of respondents, maintaining data privacy in multi-departmental settings can be challenging. The results highlight the potential for transformation that can arise from strategically aligning RPA with Big Data, but they also highlight the dangers that must be addressed in order to effectively leverage these technologies. For telecom businesses looking to maximise their use of RPA and Big Data to maintain their competitiveness in the quickly changing digital market, this paper offers insightful analysis and helpful suggestions.",
    "ISSN": "2456-5660"
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From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2024.v9.i2.pp52-71 gives all four in one JSON answer.