Das Pakanti Yadav Research Profile

About

Das Pakanati is a seasoned Sr. Oracle Cloud Techno-Functional Analyst with 14 years in Oracle ERP systems, specializing in Oracle Fusion (Cloud) and EBS (R12/11i). With over 3 years of hands-on experience with Oracle Integration Cloud (ICS/OIC), he excels in configuring, integrating, and troubleshooting Oracle applications. Das's expertise spans financials, procurement, and BI reporting, including OTBI and BIP reports, as well as data migration and process automation. He is skilled in using various adapters, REST/SOAP services, and has strong experience in BI Publisher, SmartView, and WebCenter for image processing. His technical proficiency extends to SQL, PL/SQL, Python, and AWS. Das Pakanati is an experienced Senior Oracle Cloud Techno-Functional Analyst and BIP Developer with over 16 years of expertise in the IT industry, specializing in Oracle ERP applications. His vast experience includes working on Oracle Fusion Cloud (SaaS and PaaS) and Oracle E-Business Suite (EBS) in versions R12 and 11i. With 5 years of focused experience in Oracle Fusion Cloud, Das has developed advanced skills in Oracle Integration Cloud (OIC), working with various adapters like REST, SOAP, File, FTP, Database, Oracle ERP Cloud, and Salesforce for seamless integrations. He has utilized Python scripting and integrated REST APIs in AWS environments, employing Lambda functions for automation. His technical proficiency extends to Oracle Fusion Financials, SCM, Procurement, and PPM modules, with expertise in BI Publisher, OTBI reports, and data migration through FBDI and ADF DI templates. Das has extensive knowledge in data migration for modules such as Accounts Payable, General Ledger, Fixed Assets, and Procurement, using FBDI templates for smooth data transitions. His role often involves defining ESS jobs for custom BI Publisher reports, configuring value sets, and creating data models to meet the customized reporting needs of organizations. He has worked on projects involving SmartView, Financial Reporting Studio (FRS), and WebCenter for image processing using OCR and ODR technology. As a seasoned professional, Das has hands-on experience with Oracle's Middleware products, including APM, IDM, and BPM, as well as configuring roles, user access, and chart of accounts in Oracle Cloud ERP. His technical expertise encompasses creating and managing interfaces, conversions, and customizations for financials and procurement modules, backed by deep knowledge of Oracle SQL and PL/SQL. Das’s professional journey spans multiple global organizations, where he has contributed to Oracle Cloud ERP implementations and technical solutions. He currently works at Dropbox, California, as an Oracle Cloud Technical and Integration Consultant. At Dropbox, he is involved in implementing Oracle Cloud ERP Financials and developing BI reports and integrations using OIC. Prior to this, he held similar roles at Accenture (Diebold Nixdorf), Chewy Inc., Choctaw Nation of Oklahoma, C.H. Robinson, Sherwin Williams, and Inoapps in Malaysia, handling Oracle Cloud ERP implementations across different modules. He has developed custom business processes using Oracle SOA Suite, integrating with different systems, and providing functional support to resolve critical production issues. His work includes implementing Oracle Cloud ERP for clients such as Chewy Inc., to replace legacy systems and manage financial transactions. In another key project at the Choctaw Nation of Oklahoma, Das played a pivotal role in upgrading their current JD Edwards Financials to Oracle Cloud ERP. At C.H. Robinson, he contributed to procurement and supply chain management using ICS/OIC integrations. Das also gained valuable experience working in Malaysia for Inoapps, where he specialized in Oracle Cloud Financials and Procurement for high-profile clients like GVC Projects and Silterra. Das has a strong foundation in Oracle EBS, with expertise in RICE objects, WebADI, and BPEL process activities. He has developed numerous BI Publisher reports, interfaces, and custom business processes, optimizing business workflows for various clients. His proficiency in tools such as TOAD, SQL*Developer, Service Now, and ALM further demonstrates his technical versatility. With an MBA in HR and Marketing from Sri Venkateswara University, Tirupati, and a B.Sc. in Computers, Das combines technical acumen with business knowledge to deliver effective solutions. His career reflects a commitment to continuous learning and excellence in Oracle ERP implementations and integrations across industries.

Skills

Experience

Sr. Oracle Cloud Technical & Integration Consultant & BIP Developer

Accenture, USA

Apr-2021 to Present

Education

Sri Venkateswara University, Tirupati (SVU)

MBA in HRMS and Marketing

Passout Year: 2004

Peer-Reviewed Articles

AI-Powered Automation of Cloud Database Management using Deep Reinforcement Learning and Digital Twins

With an emphasis on financial applications with extremely high performance requirements, this article explores the revolutionary combination of deep reinforcement learning and digital twin technologies for automating cloud database administration. As data volumes and query workloads increase, cloud database systems become more sophisticated, creating management challenges that conventional methods are unable to handle. A potent framework for automated management is produced by combining digital twins, which offer safe virtual replicas for training, with DRL, which enables autonomous learning through contextual interaction. Important functions, including workload management, disaster recovery procedures, resource allocation, query execution planning, compliance maintenance, and cost efficiency optimization, are all enhanced by this relationship. While administrators can do in-depth "what-if" analyses, digital twins offer safe environments for agent training. The integrated system employs phased deployment approaches, customized multi-agent architectures, and sophisticated training mechanisms, including offline reinforcement learning and curriculum learning, to guarantee reliability and safety. Technology convergence benefits financial institutions greatly by resulting in much better performance metrics, more robust systems, and reduced operating expenses while maintaining strict regulatory compliance. While federated learning techniques enable collaborative growth without compromising data privacy, explainable AI systems provide the transparency and auditability needed in financial settings.

Climate Vulnerability Assessment of Infrastructure Using Edge‑AI Integrated IoT Systems: A Survey

Climate change is amplifying extremes that directly threaten critical infrastructure. Timely, spatially resolved vulnerability assessment is indispensable for adaptation planning and operational resilience. Cloud‑first analytics alone struggle with bandwidth, latency, privacy, and continuity constraints in fast‑evolving hazards. This survey synthesizes advances at the intersection of climate vulnerability assessment, internet‑of‑things (IoT) sensing, and edge artificial intelligence (edge‑AI). We ground the assessment problem in contemporary climate risk evidence and definitions, propose an end‑to‑end framework linking hazard–exposure–vulnerability constructs to IoT/edge data flows, and review methods spanning sensing architectures, communication standards, on‑device learning (TinyML, model compression, federated learning), spatio‑temporal learning over sensor networks, and digital‑twin integration. Representative deployments in flood monitoring, structural health monitoring, and wildfire detection illustrate how edge‑AI reduces detection latency, preserves operation under degraded connectivity, and improves data stewardship—capabilities aligned with the needs of climate adaptation and risk‑informed asset management [1]–[3], [9], [10].

Scholar9 Profile ID

S9-082024-1505868

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Article Reviewed

(32)

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Mr. Das Pakanti Yadav