Building Analytics-Driven Bots: RPA Meets Business Intelligence
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V2I1P109Keywords:
RPA, Business Intelligence, Analytics, Automation, Data-Driven Bots, Process Optimization, AI, Digital Transformation, Decision-Making, Intelligent AutomationAbstract
In the present day's digital economy, businesses are under constant pressure to improve their operations, make better decisions & provide their value quickly. This has led to the combination of Robotic Process Automation (RPA) with Business Intelligence (BI). Traditional automation focuses on their speed, whereas analytics-driven RPA uses BI tools like actual time reporting, predictive analytics & data visualization to provide the context & flexibility. This link lets bots do more than just their jobs; they can also take on many other tasks that help with decision-making, managing their exceptions & improving processes over time. The paper explains how RPA works with different BI systems, looks at actual world examples from fields like banking, healthcare & government, and shows measurable results like lower operational expenses, better compliance & happier customers. This convergence marks a shift from automation serving a supporting function to acting as a strategic enabler, positioning RPA & BI not as separate initiatives but as complementary forces driving intelligent organizational transformation
References
[1] Thompson, John K., and Douglas B. Laney. Building analytics teams: harnessing analytics and artificial intelligence for business improvement. Packt Publishing Ltd, 2020.
[2] Ravi, Vadlamani, and Sk Kamaruddin. "Big data analytics enabled smart financial services: opportunities and challenges." International conference on big data analytics. Cham: Springer International Publishing, 2017.
[3] Allam, Hitesh. Exploring the Algorithms for Automatic Image Retrieval Using Sketches. Diss. Missouri Western State University, 2017.
[4] Patel, Piyushkumar. "Bonus Depreciation Loopholes: How High-Net-Worth Individuals Maximize Tax Deductions." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 1405-19.
[5] Gentsch, Peter. AI in marketing, sales and service: How marketers without a data science degree can use AI, big data and bots. springer, 2018.
[6] Wang, Liang, and Jianxin Zhao. Strategic Blueprint for Enterprise Analytics. Springer, 2020.
[7] Anand, Sangeeta. "Optimizing NoSQL Data Models for Large-Scale Health Insurance Claims Processing." International Journal of Emerging Research in Engineering and Technology 1.1 (2020): 58-66.
[8] Afriyie, Derrick. "Aligning strategic workforce planning with future-of-work trends through advanced performance management and digital HR infrastructure." 2019,
[9] Guntupalli, Bhavitha. “Clean Code in the Real World: Principles I Actually Use”. International Journal of Emerging Trends in Computer Science and Information Technology, vol. 1, no. 1, Mar. 2020, pp. 66-74
[10] Nagar, Gourav. "Leveraging Artificial Intelligence to Automate and Enhance Security Operations: Balancing Efficiency and Human Oversight." Valley International Journal Digital Library (2018): 78-94.
[11] Madanchian, Mitra, Michele Vincenti, and Hamed Taherdoost. "Redefining Leadership in the Age of AI: Tools, Applications, and Limitations." International Conference on Engineering, Applied Sciences and System Modeling. Singapore: Springer Nature Singapore, 2017.
[12] Arugula, Balkishan, and Sudhkar Gade. “Cross-Border Banking Technology Integration: Overcoming Regulatory and Technical Challenges”. International Journal of Emerging Research in Engineering and Technology, vol. 1, no. 1, Mar. 2020, pp. 40-48
[13] Ojanen, Otso, et al. "Ten Digital moves for a quick performance boost." Boston Consulting Group-BCG (2020).
[14] Jani, Parth, and Sangeeta Anand. "PEGA UM Implementation for Federal Eligibility Processing: A Case Study on Compliance Integration." JOURNAL OF RECENT TRENDS IN COMPUTER SCIENCE AND ENGINEERING (JRTCSE) 7.2 (2019): 91-108.
[15] Belharet, Adel, et al. "Report on the impact of artificial intelligence on project management." Machine Learning eJournal (2020).
[16] Patel, Piyushkumar. "The Role of AI in Forensic Accounting: Enhancing Fraud Detection Through Machine Learning." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 1420-35.
[17] Guntupalli, Bhavitha. “Code Reviews That Don’t Suck: Tips for Reviewers and Submitters”. International Journal of Emerging Research in Engineering and Technology, vol. 1, no. 2, June 2020, pp. 60-68
[18] Charan, Ram, Dominic Barton, and Dennis Carey. Talent wins: The new playbook for putting people first. Harvard Business Press, 2018.
[19] Santhosh, M. M., and Smiju Sudevan. "Artificial Intelligence in Information Technology Tools and Techniques for successful project implementation." LIBA’s Journal of Management 20 (2020).
[20] Mohammad, Abdul Jabbar. "Blockchain Ledger for Timekeeping Integrity." International Journal of Emerging Trends in Computer Science and Information Technology 1.1 (2020): 39-48.
[21] Jani, Parth, and Sarbaree Mishra. "Data Mesh in Federally Funded Healthcare Networks." The Distributed Learning and Broad Applications in Scientific Research 6 (2020): 1146-1176.
[22] Haq, Rashed. Enterprise artificial intelligence transformation. John Wiley & Sons, 2020.
[23] Shaik, Babulal. "Network Isolation Techniques in Multi-Tenant EKS Clusters." Distributed Learning and Broad Applications in Scientific Research 6 (2020).
[24] Palle, Sravanthi. "Artificial intelligence using DBS-QOS in banking organizations." Journal of scientific research & engineering trends 5.1 (2019): 107-118.
[25] Guntupalli, Bhavitha. “How I Debug Complex Issues in Large Codebases”. International Journal of Emerging Research in Engineering and Technology, vol. 1, no. 1, Mar. 2020, pp. 67-76
[26] Patel, Piyushkumar, and Hetal Patel. "Developing a Risk Management Framework for Cybersecurity in Financial Reporting." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 1436-51.
[27] Gentsch, Peter. "AI business: framework and maturity model." AI in Marketing, Sales and Service: How Marketers without a Data Science Degree can use AI, Big Data and Bots. Cham: Springer International Publishing, 2018. 27-78.
[28] Sharma, Pranjal. Kranti Nation: India and the fourth industrial revolution. Pan Macmillan, 2017.
