SCALABLE ETL PIPELINES FOR TELECOM BILLING SYSTEMS: A COMPARATIVE STUDY

Authors

  • Balachandar Paulraj Independent Researcher, USA

DOI:

https://doi.org/10.36676/dira.v12.i3.107

Keywords:

ETL, Telecom environment, TELECOM BILLING SYSTEMS

Abstract

This paper aims at comparing the following scalable ETL processes that are used in telecom billing systems. Telecom environment requires the use of ETL pipelines to process huge amounts of data for billing and other data related functions. This analysis covers various types of ETL solutions such as batch, streaming and cloud based ETL techniques. There are several parameters which have been considered while analyzing the issue including scalability, performance, cost and precision. The results indicate that streaming ETL pipelines come as more efficient in real-time data processing, in contrast to batch-based pipelines for large historical data. While on the cloud, the solutions can accommodate the growing number of users and new technologies, but at a cost. This paper concludes that there is merit in the adoption of different ETL techniques in that it enables telecom organizations to achieve the best results in billing. The future trend involves the use of artificial intelligence in ETL, enhanced security aspects, comparison between serverless, and hybrid cloud ETL solutions.

References

Abdel-Rahman, M. and Younis, F.A., 2022. Developing an Architecture for Scalable Analytics in a Multi-Cloud Environment for Big Data-Driven Applications. International Journal of Business Intelligence and Big Data Analytics, 5(1), pp.66-73.

Biswas, N., 2022. Modeling, analysis and simulation of near real-time ETL processes of big data in cloud.

Clair, K.L.S.S., Pineda, E. and Garcia, E., 2020. A study to evaluate the success of digicel's mind billing system on its internal users. Journal of MIS@ UB, 4(1).

Damus Ros, N., 2023. A Business Intelligence Solution, based on a Big Data Architecture, for processing and analyzing the World Bank data.

Khan, B., Jan, S., Khan, W. and Chughtai, M.I., 2024. An Overview of ETL Techniques, Tools, Processes and Evaluations in Data Warehousing. Journal on Big Data, 6.

Mendoza Sánchez, J.L., 2021. Design and implementation of a data aggregation system for the 5G network management plane (Doctoral dissertation, Telecomunicacion).

Muddasir, M., Raghuveer, K. and Dayanand, R., 2021. Towards comparative analysis of resumption techniques in ETL. Indonesian Journal of Information Systems, 3(2), pp.82-93.

Munappy, A.R., Dakkak, A., Bosch, J., Olsson, H. and Ericsson, T.L., 2024. Bidirectional Data Pipelines: An Industrial Case Study.

Qaiser, A., Farooq, M.U., Mustafa, S.M.N. and Abrar, N., 2023. Comparative analysis of ETL tools in big data analytics. Pakistan Journal of Engineering and Technology, 6(1), pp.7-12.

Tahir, S., 2020. Data analytics on Telecom Dataset (Doctoral dissertation, Quaid I Azam University).

Tran, T., 2024. In-depth Analysis and Evaluation of ETL Solutions for Big Data Processing.

Zeydan, E. and Mangues-Bafalluy, J., 2022. Recent advances in data engineering for networking. IEEE Access, 10, pp.34449-34496.

Santhosh Palavesh. (2019). The Role of Open Innovation and Crowdsourcing in Generating New Business Ideas and Concepts. International Journal for Research Publication and Seminar, 10(4), 137–147. https://doi.org/10.36676/jrps.v10.i4.1456

Santosh Palavesh. (2021). Developing Business Concepts for Underserved Markets: Identifying and Addressing Unmet Needs in Niche or Emerging Markets. Innovative Research Thoughts, 7(3), 76–89. https://doi.org/10.36676/irt.v7.i3.1437

Palavesh, S. (2021). Co-Creating Business Concepts with Customers: Approaches to the Use of Customers in New Product/Service Development. Integrated Journal for Research in Arts and Humanities, 1(1), 54–66. https://doi.org/10.55544/ijrah.1.1.9

Santhosh Palavesh. (2022). Entrepreneurial Opportunities in the Circular Economy: Defining Business Concepts for Closed-Loop Systems and Resource Efficiency. European Economic Letters (EEL), 12(2), 189–204. https://doi.org/10.52783/eel.v12i2.1785

Santhosh Palavesh. (2022). The Impact of Emerging Technologies (e.g., AI, Blockchain, IoT) On Conceptualizing and Delivering new Business Offerings. International Journal on Recent and Innovation Trends in Computing and Communication, 10(9), 160–173. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10955

Palavesh, S. (2024). Developing sustainable business concepts: Integrating environmental, social, and economic considerations into new venture ideation. African Journal of Biological Sciences, 6(14), 3025-3043. https://doi.org/10.48047/AFJBS.6.14.2024.3025-3043

Santhosh Palavesh. (2021). Business Model Innovation: Strategies for Creating and Capturing Value Through Novel Business Concepts. European Economic Letters (EEL), 11(1). https://doi.org/10.52783/eel.v11i1.1784

Santhosh Palavesh. (2023). Leveraging Lean Startup Principles: Developing And Testing Minimum Viable Products (Mvps) In New Business Ventures. Educational Administration: Theory and Practice, 29(4), 2418–2424. https://doi.org/10.53555/kuey.v29i4.7141

Palavesh, S. (2023). The role of design thinking in conceptualizing and validating new business ideas. Journal of Informatics Education and Research, 3(2), 3057.

Santhosh Palavesh. (2024). Identifying Market Gaps and Unmet Customer Needs: A Framework for Ideating Innovative Business Concepts. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 1067 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6612

Vijaya Venkata Sri Rama Bhaskar, Akhil Mittal, Santosh Palavesh, Krishnateja Shiva, Pradeep Etikani. (2020). Regulating AI in Fintech: Balancing Innovation with Consumer Protection. European Economic Letters (EEL), 10(1). https://doi.org/10.52783/eel.v10i1.1810

Sri Sai Subramanyam Challa. (2023). Regulatory Intelligence: Leveraging Data Analytics for Regulatory Decision-Making. International Journal on Recent and Innovation Trends in Computing and Communication, 11(11), 1426–1434. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10893

Sri Sai Subramanyam Challa. (2024). Leveraging AI for Risk Management in Computer System Validation. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(2), 145–153. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/95

Challa, S. S. S. (2020). Assessing the regulatory implications of personalized medicine and the use of biomarkers in drug development and approval. European Chemical Bulletin, 9(4), 134-146.

D.O.I10.53555/ecb.v9:i4.17671

EVALUATING THE EFFECTIVENESS OF RISK-BASED APPROACHES IN STREAMLINING THE REGULATORY APPROVAL PROCESS FOR NOVEL THERAPIES. (2021). Journal of Population Therapeutics and Clinical Pharmacology, 28(2), 436-448. https://doi.org/10.53555/jptcp.v28i2.7421

Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of Pharma Research, 7(5), 380-387.

Tilala, M., Challa, S. S. S., Chawda, A. D., Benke, A. P., & Sharma, S. (2024). Analyzing the role of real-world evidence (RWE) in supporting regulatory decision-making and post-marketing surveillance. African Journal of Biological Sciences, 6(14), 3060-3075. https://doi.org/10.48047/AFJBS.6.14.2024.3060-3075

Ashok Choppadandi. (2022). Exploring the Potential of Blockchain Technology in Enhancing Supply Chain Transparency and Compliance with Good Distribution Practices (GDP). International Journal on Recent and Innovation Trends in Computing and Communication, 10(12), 336–343. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10981

Challa, S. S. S., Chawda, A. D., Benke, A. P., & Tilala, M. (2020). Evaluating the use of machine learning algorithms in predicting drug-drug interactions and adverse events during the drug development process. NeuroQuantology, 18(12), 176-186. https://doi.org/10.48047/nq.2020.18.12.NQ20252

Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2023). Investigating the impact of AI-assisted drug discovery on the efficiency and cost-effectiveness of pharmaceutical R&D. Journal of Cardiovascular Disease Research, 14(10), 2244.

Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2022). Quality Management Systems in Regulatory Affairs: Implementation Challenges and Solutions. Journal for Research in Applied Sciences and Biotechnology, 1(3), 278–284. https://doi.org/10.55544/jrasb.1.3.36

Challa, S. S. S., Chawda, A. D., Benke, A. P., & Tilala, M. (2024). Streamlining Change Control Processes in Regulatory Affairs: Best Practices and Case Studies. Integrated Journal for Research in Arts and Humanities, 4(4), 67–75. https://doi.org/10.55544/ijrah.4.4.12

Harshita Cherukuri. (2024). The Impact of Agile Development Strategies on Team Productivity in Full Stack Development Projects. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 175 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6407

Ranjit Kumar Gupta, Sagar Shukla, Anaswara Thekkan Rajan, & Sneha Aravind. (2022). Leveraging Data Analytics to Improve User Satisfaction for Key Personas: The Impact of Feedback Loops. International Journal for Research Publication and Seminar, 11(4), 242–252. https://doi.org/10.36676/jrps.v11.i4.1489

Ranjit Kumar Gupta, Harshita Cherukuri, Sagar Shukla, Anaswara Thekkan Rajan, Sneha Aravind. (2024). Deploying Containerized Microservices in on-Premise Kubernetes Environments: Challenges and Best Practices. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(2), 74–90. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/86

Ranjit Kumar Gupta, Sagar Shukla, Anaswara Thekkan Rajan, Sneha Aravind, 2021. "Utilizing Splunk for Proactive Issue Resolution in Full Stack Development Projects" ESP Journal of Engineering & Technology Advancements 1(1): 57-64.

Ranjit Kumar Gupta, Sagar Shukla, Anaswara Thekkan Rajan, Sneha Aravind, Ashok Choppadandi. (2024). Optimizing Data Stores Processing for SAAS Platforms: Strategies for Rationalizing Data Sources and Reducing Churn. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(2), 176–197. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/99

Sagar Shukla, Anaswara Thekkan Rajan, Sneha Aravind, Ranjit Kumar Gupta, Santosh Palavesh. (2023). Monetizing API Suites: Best Practices for Establishing Data Partnerships and Iterating on Customer Feedback. European Economic Letters (EEL), 13(5), 2040–2053. https://doi.org/10.52783/eel.v13i5.1798

Aravind, S., Cherukuri, H., Gupta, R. K., Shukla, S., & Rajan, A. T. (2022). The role of HTML5 and CSS3 in creating optimized graphic prototype websites and application interfaces. NeuroQuantology, 20(12), 4522-4536. https://doi.org/10.48047/NQ.2022.20.12.NQ77775

Sneha Aravind, Ranjit Kumar Gupta, Sagar Shukla, & Anaswara Thekkan Rajan. (2024). Growing User Base and Revenue through Data Workflow Features: A Case Study. International Journal of Communication Networks and Information Security (IJCNIS), 16(1 (Special Issue), 436–455. Retrieved from https://www.ijcnis.org/index.php/ijcnis/article/view/6832

Alok Gupta. (2024). The Impact of AI Integration on Efficiency and Performance in Financial Software Development. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 185–193. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6408

Ugandhar Dasi, Nikhil Singla, Rajkumar Balasubramanian, Siddhant Benadikar, Rishabh Rajesh Shanbhag. (2024). Privacy-Preserving Machine Learning Techniques: Balancing Utility and Data Protection. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(2), 251–261. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/107

Ugandhar Dasi. (2024). Developing A Cloud-Based Natural Language Processing (NLP) Platform for Sentiment Analysis and Opinion Mining of Social Media Data. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 165–174. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6406

Ugandhar Dasi. (2024). Developing A Cloud-Based Natural Language Processing (NLP) Platform for Sentiment Analysis and Opinion Mining of Social Media Data. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 165–174. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6406

Dasi, U., Singla, N., Balasubramanian, R., Benadikar, S., & Shanbhag, R. R. (2024). Ethical implications of AI-driven personalization in digital media. Journal of Informatics Education and Research, 4(3), 588-593.

Nikhil Singla. (2023). Assessing the Performance and Cost-Efficiency of Serverless Computing for Deploying and Scaling AI and ML Workloads in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 618–630. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6730

Ugandhar Dasi, Nikhil Singla, Rajkumar Balasubramanian, Siddhant Benadikar, Rishabh Rajesh Shanbhag. (2024). Analyzing the Security and Privacy Challenges in Implementing Ai and Ml Models in Multi-Tenant Cloud Environments. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(2), 262–270. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/108

Balasubramanian, R., Benadikar, S., Shanbhag, R. R., Dasi, U., & Singla, N. (2024). Investigating the application of reinforcement learning algorithms for autonomous resource management in cloud computing environments. African Journal of Biological Sciences, 6(14), 6451-6480. https://doi.org/10.48047/AFJBS.6.14.2024.6451-6480

Rishabh Rajesh Shanbhag, Rajkumar Balasubramanian, Ugandhar Dasi, Nikhil Singla, & Siddhant Benadikar. (2022). Case Studies and Best Practices in Cloud-Based Big Data Analytics for Process Control. International Journal for Research Publication and Seminar, 13(5), 292–311. https://doi.org/10.36676/jrps.v13.i5.1462

Siddhant Benadikar. (2021). Developing a Scalable and Efficient Cloud-Based Framework for Distributed Machine Learning. International Journal of Intelligent Systems and Applications in Engineering, 9(4), 288 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6761

Siddhant Benadikar. (2021). Evaluating the Effectiveness of Cloud-Based AI and ML Techniques for Personalized Healthcare and Remote Patient Monitoring. International Journal on Recent and Innovation Trends in Computing and Communication, 9(10), 03–16. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11036

Shanbhag, R. R., Benadikar, S., Dasi, U., Singla, N., & Balasubramanian, R. (2024). Investigating the application of transfer learning techniques in cloud-based AI systems for improved performance and reduced training time. Letters in High Energy Physics, 31.

Rishabh Rajesh Shanbhag. (2023). Exploring the Use of Cloud-Based AI and ML for Real-Time Anomaly Detection and Predictive Maintenance in Industrial IoT Systems. International Journal of Intelligent Systems and Applications in Engineering, 11(4), 925 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6762

Nikhil Singla. (2023). Assessing the Performance and Cost-Efficiency of Serverless Computing for Deploying and Scaling AI and ML Workloads in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 618–630. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/673

Nikhil Singla. (2023). Assessing the Performance and Cost-Efficiency of Serverless Computing for Deploying and Scaling AI and ML Workloads in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 618–630. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6730

Challa, S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of PharmaResearch, 7(5), 380-387.

Chaturvedi, R., & Sharma, S. (2024). Implementing Predictive Analytics for Proactive Revenue Cycle Management. Journal for Research in Applied Sciences and Biotechnology, 3(4), 74–78. https://doi.org/10.55544/jrasb.3.4.9

Chaturvedi, R., Sharma, S., Pandian, P. K. G., & Sharma, S. (2024). Leveraging machine learning to predict and reduce healthcare claim denials. Zenodo. https://doi.org/10.5281/zenodo.13268360

Ritesh Chaturvedi. (2023). Robotic Process Automation (RPA) in Healthcare: Transforming Revenue Cycle Operations. International Journal on Recent and Innovation Trends in Computing and Communication, 11(6), 652–658. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11045

Chaturvedi, R., & Sharma, S. (2022). Assessing the Long-Term Benefits of Automated Remittance in Large Healthcare Networks. Journal for Research in Applied Sciences and Biotechnology, 1(5), 219–224. https://doi.org/10.55544/jrasb.1.5.25

Chaturvedi, R., & Sharma, S. (2022). Enhancing healthcare staffing efficiency with AI-powered demand management tools. Eurasian Chemical Bulletin, 11(Regular Issue 1), 675-681. https://doi.org/10.5281/zenodo.13268360

Dr. Saloni Sharma, & Ritesh Chaturvedi. (2017). Blockchain Technology in Healthcare Billing: Enhancing Transparency and Security. International Journal for Research Publication and Seminar, 10(2), 106–117. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1475

Dr. Saloni Sharma, & Ritesh Chaturvedi. (2017). Blockchain Technology in Healthcare Billing: Enhancing Transparency and Security. International Journal for Research Publication and Seminar, 10(2), 106–117. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1475

Saloni Sharma. (2020). AI-Driven Predictive Modelling for Early Disease Detection and Prevention. International Journal on Recent and Innovation Trends in Computing and Communication, 8(12), 27–36. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11046

Chaturvedi, R., & Sharma, S. (2022). Assessing the Long-Term Benefits of Automated Remittance in Large Healthcare Networks. Journal for Research in Applied Sciences and Biotechnology, 1(5), 219–224. https://doi.org/10.55544/jrasb.1.5.25

Pavan Ogeti. (2024). Benefits and Challenges of Deploying Machine Learning Models in the Cloud. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 194–209. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6409

Pavan Ogeti, Narendra Sharad Fadnavis, Gireesh Bhaulal Patil, Uday Krishna Padyana, Hitesh Premshankar Rai. (2022). Blockchain Technology for Secure and Transparent Financial Transactions. European Economic Letters (EEL), 12(2), 180–188. Retrieved from https://www.eelet.org.uk/index.php/journal/article/view/1283

Ogeti, P., Fadnavis, N. S., Patil, G. B., Padyana, U. K., & Rai, H. P. (2023). Edge computing vs. cloud computing: A comparative analysis of their roles and benefits. Volume 20, No. 3, 214-226.

Fadnavis, N. S., Patil, G. B., Padyana, U. K., Rai, H. P., & Ogeti, P. (2020). Machine learning applications in climate modeling and weather forecasting. NeuroQuantology, 18(6), 135-145. https://doi.org/10.48047/nq.2020.18.6.NQ20194

Narendra Sharad Fadnavis. (2021). Optimizing Scalability and Performance in Cloud Services: Strategies and Solutions. International Journal on Recent and Innovation Trends in Computing and Communication, 9(2), 14–21. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10889

Gireesh Bhaulal Patil. (2022). AI-Driven Cloud Services: Enhancing Efficiency and Scalability in Modern Enterprises. International Journal of Intelligent Systems and Applications in Engineering, 10(1), 153–162. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6728

Padyana, U. K., Rai, H. P., Ogeti, P., Fadnavis, N. S., & Patil, G. B. (2023). AI and Machine Learning in Cloud-Based Internet of Things (IoT) Solutions: A Comprehensive Review and Analysis. Integrated Journal for Research in Arts and Humanities, 3(3), 121–132. https://doi.org/10.55544/ijrah.3.3.20

Patil, G. B., Padyana, U. K., Rai, H. P., Ogeti, P., & Fadnavis, N. S. (2021). Personalized marketing strategies through machine learning: Enhancing customer engagement. Journal of Informatics Education and Research, 1(1), 9. http://jier.org

Padyana, U. K., Rai, H. P., Ogeti, P., Fadnavis, N. S., & Patil, G. B. (2023). AI and Machine Learning in Cloud-Based Internet of Things (IoT) Solutions: A Comprehensive Review and Analysis. Integrated Journal for Research in Arts and Humanities, 3(3), 121–132. https://doi.org/10.55544/ijrah.3.3.20

Padyana, U. K., Rai, H. P., Ogeti, P., Fadnavis, N. S., & Patil, G. B. (2024). Predicting disease susceptibility with machine learning in genomics. Letters in High Energy Physics, 2024(20).

Uday Krishna Padyana, Hitesh Premshankar Rai, Pavan Ogeti, Narendra Sharad Fadnavis, & Gireesh Bhaulal Patil. (2024). Server less Architectures in Cloud Computing: Evaluating Benefits and Drawbacks. Innovative Research Thoughts, 6(3), 1–12. https://doi.org/10.36676/irt.v10.i3.1439

Rai, H. P., Ogeti, P., Fadnavis, N. S., Patil, G. B., & Padyana, U. K. (2024). AI-based forensic analysis of digital images: Techniques and applications in cybersecurity. Journal of Digital Economy, 2(1), 47-61.

Hitesh Premshankar Rai, Pavan Ogeti, Narendra Sharad Fadnavis, Gireesh Bhaulal Patil, & Uday Krishna Padyana. (2024). Integrating Public and Private Clouds: The Future of Hybrid Cloud Solutions. Universal Research Reports, 8(2), 143–153. https://doi.org/10.36676/urr.v9.i4.1320

Hitesh Premshankar Rai, Pavan Ogeti, Narendra Sharad Fadnavis, Gireesh Bhaulal Patil, & Uday Krishna Padyana. (2024). Integrating Public and Private Clouds: The Future of Hybrid Cloud Solutions. Universal Research Reports, 8(2), 143–153. https://doi.org/10.36676/urr.v9.i4.1320

Ugandhar Dasi. (2024). Developing A Cloud-Based Natural Language Processing (NLP) Platform for Sentiment Analysis and Opinion Mining of Social Media Data. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 165–174. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6406

Dasi, U., Singla, N., Balasubramanian, R., Benadikar, S., & Shanbhag, R. R. (2024). Ethical implications of AI-driven personalization in digital media. Journal of Informatics Education and Research, 4(3), 588-593.

Krishnateja Shiva. (2024). Natural Language Processing for Customer Service Chatbots: Enhancing Customer Experience. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 155–164. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6405

Krishnateja Shiva. (2022). Leveraging Cloud Resource for Hyperparameter Tuning in Deep Learning Models. International Journal on Recent and Innovation Trends in Computing and Communication, 10(2), 30–35. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10980

Shiva, K., Etikani, P., Bhaskar, V. V. S. R., Palavesh, S., & Dave, A. (2022). The rise of robo-advisors: AI-powered investment management for everyone. Journal of Namibian Studies, 31, 201-214.

Etikani, P., Bhaskar, V. V. S. R., Choppadandi, A., Dave, A., & Shiva, K. (2024). Forecasting climate change with deep learning: Improving climate modeling accuracy. African Journal of Bio-Sciences, 6(14), 3903-3918. https://doi.org/10.48047/AFJBS.6.14.2024.3903-3918

Etikani, P., Bhaskar, V. V. S. R., Nuguri, S., Saoji, R., & Shiva, K. (2023). Automating machine learning workflows with cloud-based pipelines. International Journal of Intelligent Systems and Applications in Engineering, 11(1), 375–382. https://doi.org/10.48047/ijisae.2023.11.1.375

Etikani, P., Bhaskar, V. V. S. R., Palavesh, S., Saoji, R., & Shiva, K. (2023). AI-powered algorithmic trading strategies in the stock market. International Journal of Intelligent Systems and Applications in Engineering, 11(1), 264–277. https://doi.org/10.1234/ijsdip.org_2023-Volume-11-Issue-1_Page_264-277

Shiva, K., Etikani, P., Bhaskar, V. V. S. R., Mittal, A., Dave, A., Thakkar, D., Kanchetti, D., & Munirathnam, R. (2024). Anomaly detection in sensor data with machine learning: Predictive maintenance for industrial systems. J. Electrical Systems, 20-10s, 454–462.

Bhaskar, V. V. S. R., Etikani, P., Shiva, K., Choppadandi, A., & Dave, A. (2019). Building explainable AI systems with federated learning on the cloud. Journal of Cloud Computing and Artificial Intelligence, 16(1), 1–14.

Ogeti, P., Fadnavis, N. S., Patil, G. B., Padyana, U. K., & Rai, H. P. (2022). Blockchain technology for secure and transparent financial transactions. European Economic Letters, 12(2), 180-192. http://eelet.org.uk

Vijaya Venkata Sri Rama Bhaskar, Akhil Mittal, Santosh Palavesh, Krishnateja Shiva, Pradeep Etikani. (2020). Regulating AI in Fintech: Balancing Innovation with Consumer Protection. European Economic Letters (EEL), 10(1). https://doi.org/10.52783/eel.v10i1.1810

Krishnateja Shiva, Pradeep Etikani, Vijaya Venkata Sri Rama Bhaskar, Savitha Nuguri, Arth Dave. (2024). Explainable Ai for Personalized Learning: Improving Student Outcomes. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(2), 198–207. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/100

Dave, A., Shiva, K., Etikani, P., Bhaskar, V. V. S. R., & Choppadandi, A. (2022). Serverless AI: Democratizing machine learning with cloud functions. Journal of Informatics Education and Research, 2(1), 22-35. http://jier.org

Dave, A., Etikani, P., Bhaskar, V. V. S. R., & Shiva, K. (2020). Biometric authentication for secure mobile payments. Journal of Mobile Technology and Security, 41(3), 245-259.

Saoji, R., Nuguri, S., Shiva, K., Etikani, P., & Bhaskar, V. V. S. R. (2021). Adaptive AI-based deep learning models for dynamic control in software-defined networks. International Journal of Electrical and Electronics Engineering (IJEEE), 10(1), 89–100. ISSN (P): 2278–9944; ISSN (E): 2278–9952

Narendra Sharad Fadnavis. (2021). Optimizing Scalability and Performance in Cloud Services: Strategies and Solutions. International Journal on Recent and Innovation Trends in Computing and Communication, 9(2), 14–21. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10889

Varun Nakra. (2023). Enhancing Software Project Management and Task Allocation with AI and Machine Learning. International Journal on Recent and Innovation Trends in Computing and Communication, 11(11), 1171–1178. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10684

Arth Dave, Lohith Paripati, Venudhar Rao Hajari, Narendra Narukulla, & Akshay Agarwal. (2024). Future Trends: The Impact of AI and ML on Regulatory Compliance Training Programs. Universal Research Reports, 11(2), 93–101. Retrieved from https://urr.shodhsagar.com/index.php/j/article/view/1257

Joel lopes, Arth Dave, Hemanth Swamy, Varun Nakra, & Akshay Agarwal. (2023). Machine Learning Techniques And Predictive Modeling For Retail Inventory Management Systems. Educational Administration: Theory and Practice, 29(4), 698–706. https://doi.org/10.53555/kuey.v29i4.5645

Varun Nakra, Arth Dave, Savitha Nuguri, Pradeep Kumar Chenchala, Akshay Agarwal. (2023). Robo-Advisors in Wealth Management: Exploring the Role of AI and ML in Financial Planning. European Economic Letters (EEL), 13(5), 2028–2039. Retrieved from https://www.eelet.org.uk/index.php/journal/article/view/1514

Akhil Mittal, Pandi Kirupa Gopalakrishna Pandian. (2023). Adversarial Machine Learning for Robust Intrusion Detection Systems. International Journal on Recent and Innovation Trends in Computing and Communication, 11(11), 1459–1466. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10918

Tripathi, A. (2019). Serverless architecture patterns: Deep dive into event-driven, microservices, and serverless APIs. International Journal of Creative Research Thoughts (IJCRT), 7(3), 234-239. Retrieved from http://www.ijcrt.org

Bellapukonda, P., Vijaya, G., Subramaniam, S., & Chidambaranathan, S. (2024). Security and optimization in IoT networks using AI-powered digital twins. In Harnessing AI and Digital Twin Technologies in Businesses (p. 14). https://doi.org/10.4018/979-8-3693-3234-4.ch024

E. A. Banu, S. Chidambaranathan, N. N. Jose, P. Kadiri, R. E. Abed and A. Al-Hilali, "A System to Track the Behaviour or Pattern of Mobile Robot Through RNN Technique," 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 2024, pp. 2003-2005, doi: 10.1109/ICACITE60783.2024.10617430.

Patil, Y. M., Abraham, A. R., Chaubey, N. K., Baskar, K., & Chidambaranathan, S. (2024). A comparative analysis of machine learning techniques in creating virtual replicas for healthcare simulations. In Harnessing AI and Digital Twin Technologies in Businesses (p. 12). https://doi.org/10.4018/979-8-3693-3234-4.ch002

George, B., Oswal, N., Baskar, K., & Chidambaranathan, S. (2024). Innovative approaches to simulating human-machine interactions through virtual counterparts. In Harnessing AI and Digital Twin Technologies in Businesses (p. 11). https://doi.org/10.4018/979-8-3693-3234-4.ch018

Charaan, R. M. D., Chidambaranathan, S., Jothivel, K. M., Subramaniam, S., & Prabu, M. (2024). Machine learning-driven data fusion in wireless sensor networks with virtual replicas: A comprehensive evaluation. In Harnessing AI and Digital Twin Technologies in Businesses (p. 11). https://doi.org/10.4018/979-8-3693-3234-4.ch020

Ayyavaraiah, M., Jeyakumar, B., Chidambaranathan, S., Subramaniam, S., Anitha, K., & Sangeetha, A. (2024). Smart transportation systems: Machine learning application in WSN-based digital twins. In Harnessing AI and Digital Twin Technologies in Businesses (p. 11). https://doi.org/10.4018/979-8-3693-3234-4.ch026

Venkatesan, B., Mannanuddin, K., Chidambaranathan, S., Jeyakumar, B., Rayapati, B. R., & Baskar, K. (2024). Deep learning safeguard: Exploring GANs for robust security in open environments. In Enhancing Security in Public Spaces Through Generative Adversarial Networks (GANs) (p. 14). https://doi.org/10.4018/979-8-3693-3597-0.ch009

P. V, V. R and S. Chidambaranathan, "Polyp Segmentation Using UNet and ENet," 2023 6th International Conference on Recent Trends in Advance Computing (ICRTAC), Chennai, India, 2023, pp. 516-522, doi: 10.1109/ICRTAC59277.2023.10480851.

Athisayaraj, A. A., Sathiyanarayanan, M., Khan, S., Selvi, A. S., Briskilla, M. I., Jemima, P. P., Chidambaranathan, S., Sithik, A. S., Sivasankari, K., & Duraipandian, K. (2023). Smart thermal-cooler umbrella (UK Design No. 6329357).

Krishnateja Shiva. (2024). Natural Language Processing for Customer Service Chatbots: Enhancing Customer Experience. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 155–164. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6405

Shiva, K., Etikani, P., Bhaskar, V. V. S. R., Mittal, A., Dave, A., Thakkar, D., Kanchetti, D., & Munirathnam, R. (2024). Anomaly detection in sensor data with machine learning: Predictive maintenance for industrial systems. Journal of Electrical Systems, 20(10s), 454-462.

Kanchetti, D., Munirathnam, R., & Thakkar, D. (2024). Integration of Machine Learning Algorithms with Cloud Computing for Real-Time Data Analysis. Journal for Research in Applied Sciences and Biotechnology, 3(2), 301–306. https://doi.org/10.55544/jrasb.3.2.46

Challa, S. S. S., Chawda, A. D., Benke, A. P., & Tilala, M. (2023). Regulatory intelligence: Leveraging data analytics for regulatory decision-making. International Journal on Recent and Innovation Trends in Computing and Communication, 11, 10.

Challa, S. S. S., Chawda, A. D., Benke, A. P., & Tilala, M. (2024). Streamlining change control processes in regulatory affairs: Best practices and case studies. Integrated Journal for Research in Arts and Humanities, 4(4), 4.

Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of Pharma Research, 7(5),

Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2021). Navigating regulatory requirements for complex dosage forms: Insights from topical, parenteral, and ophthalmic products. NeuroQuantology, 19(12), 15.

Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2022). Quality management systems in regulatory affairs: Implementation challenges and solutions. Journal for Research in Applied Sciences and Biotechnology, 1(3),

Gajera, B., Shah, H., Parekh, B., Rathod, V., Tilala, M., & Dave, R. H. (2024). Design of experiments-driven optimization of spray drying for amorphous clotrimazole nanosuspension. AAPS PharmSciTech, 25(6),

Hajari, V. R., Chaturvedi, R., Sharma, S., Tilala, M., & Chawda, A. D. (2024). Risk-based testing methodologies for FDA compliance in medical devices. African Journal of Biological Sciences, 6(4),

Tilala, M. (2023). Real-time data processing in healthcare: Architectures and applications for immediate clinical insights. International Journal on Recent and Innovation Trends in Computing and Communication, 11, 20.

Tilala, M. H., Chenchala, P. K., Choppadandi, A., Kaur, J., Naguri, S., Saoji, R., & ... (2024). Ethical considerations in the use of artificial intelligence and machine learning in health care: A comprehensive review. Cureus, 16(6), 2.

Tilala, M., & Chawda, A. D. (2020). Evaluation of compliance requirements for annual reports in pharmaceutical industries. NeuroQuantology, 18(11), 27.

Tilala, M., Challa, S. S. S., Chawda, A. D., Pandurang, A., & Benke, D. S. S. (2024). Analyzing the role of real-world evidence (RWE) in supporting regulatory decision-making and post-marketing surveillance. African Journal of Biological Sciences, 6(14),

Tilala, M., Chawda, A. D., & Benke, A. P. (2023). Enhancing regulatory compliance through training and development programs: Case studies and recommendations. Journal of Cardiovascular Research, 14(11),

Ashok Choppadandi, Jagbir Kaur, Pradeep Kumar Chenchala, Akshay Agarwal, Varun Nakra, Pandi Kirupa Gopalakrishna Pandian, 2021. "Anomaly Detection in Cybersecurity: Leveraging Machine Learning Algorithms" ESP Journal of Engineering & Technology Advancements 1(2): 34-41.

Shashwat Agrawal, Raja Kumar Kolli, Shanmukha Eeti, Prof.(Dr.) Punit Goel, & Prof.(Dr.) Arpit Jain. (2024). Impact of Lean Six Sigma on Operational Efficiency in Supply Chain Management. Darpan International Research Analysis, 12(3), 420–434. https://doi.org/10.36676/dira.v12.i3.99

Complex Load Balancing in Multi-Regional Networks , IJNTI - INTERNATIONAL JOURNAL OF NOVEL TRENDS AND INNOVATION (www.IJNTI.org), ISSN:2984-908X, Vol.2, Issue 1, page no.a19-a29, January-2024, Available :https://rjpn.org/IJNTI/papers/IJNTI2401004.pdf

Palo Alto Firewalls: Security in Enterprise Networks , IJEDR - INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH (www.IJEDR.org), ISSN:2321-9939, Vol.12, Issue 3, page no.1-13, August-2024, Available :https://rjwave.org/IJEDR/papers/IJEDR200A001.pdf

Kolli, R. K., Chhapola, A., & Kaushik, S. (2022). Arista 7280 switches: Performance in national data centers. TIJER - International Research Journal , 9 (7), 95-106.

Kolli, R. K., Goel, O., & Kumar, L. (2021). Enhanced network efficiency in telecoms. International Journal of Current Science , 11 (3), 29-43.

Kolli, R. K., Goel, O., & Kumar, L. (2021). Enhanced network efficiency in telecoms. International Journal of Current Science , 11 (3), 29-43.

The Role of RPA and AI in Automating Business Processes in Large Corporations , IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.e784-e799, March-2023, Available :https://ijnrd.org/papers/IJNRD2303502.pdf

Achieving Revenue Recognition Compliance: A Study of ASC606 vs. IFRS15 , International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 7, page no.h278-h295, July-2022, Available :http://www.jetir.org/papers/JETIR2207742.pdf

ER. AMIT MANGAL,DR. PRERNA GUPTA, Comparative Analysis of Optimizing SAP S/4HANA in Large Enterprises , International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 4, pp.j367-j379, April 2023, Available at :http://www.ijcrt.org/papers/IJCRT23A4209.pdf

Downloads

Published

2024-09-20
CITATION
DOI: 10.36676/dira.v12.i3.107
Published: 2024-09-20

How to Cite

Balachandar Paulraj. (2024). SCALABLE ETL PIPELINES FOR TELECOM BILLING SYSTEMS: A COMPARATIVE STUDY. Darpan International Research Analysis, 12(3), 555–573. https://doi.org/10.36676/dira.v12.i3.107