Raghav Agarwal’s scientific contributions

What is this page?


This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.

Publications (37)


Impact of Dynamic Pricing in SAP SD on Global Trade Compliance
  • Research Proposal
  • File available

January 2025

·

27 Reads

·

Narrain Prithvi Dharuman

·

·

[...]

·

Raghav Agarwal

Dynamic pricing, a critical component of modern business strategies, has transformed global trade by introducing agility and responsiveness to market fluctuations. In the context of SAP Sales and Distribution (SD), the integration of dynamic pricing mechanisms has profound implications for global trade compliance. This study explores the interplay between dynamic pricing models in SAP SD and the regulatory frameworks governing international trade. Dynamic pricing enables businesses to optimize revenue by adjusting prices in real-time based on demand, competition, and external factors. While this approach drives profitability, it introduces complexities in adhering to trade compliance requirements, such as anti-dumping regulations, export control laws, and tax compliance. SAP SD, a robust enterprise resource planning (ERP) module, facilitates dynamic pricing but requires precise configuration to ensure compliance with international trade laws. The research identifies key challenges such as aligning real-time pricing strategies with customs valuation methods, managing country-specific tax policies, and ensuring accurate documentation for cross-border transactions. It also highlights the role of automation and compliance checks within SAP SD to mitigate risks associated with regulatory breaches. Through a detailed analysis, the study demonstrates how organizations can leverage SAP SD's capabilities to balance pricing flexibility with legal adherence. Recommendations include implementing advanced analytics for risk assessment, regular system audits, and training for compliance teams. By addressing these challenges, companies can achieve sustainable growth in global markets while maintaining ethical and legal standards. This paper underscores the importance of integrating technology with compliance frameworks, ensuring seamless operations in an increasingly complex global trade environment.

Download

Resagate Global-Academy for International Journals of Multidisciplinary Research Automating Data Transformation with SAP MDG for Consistent Master Data Management

January 2025

·

19 Reads

In today's data-driven landscape, organizations face the challenge of maintaining consistent and accurate master data across diverse systems. Automating data transformation using SAP Master Data Governance (MDG) offers a strategic approach to streamline master data management processes. This paper explores the capabilities of SAP MDG in automating the transformation of master data to ensure its integrity and consistency across enterprise applications. The implementation of automated workflows within SAP MDG facilitates real-time data validation, integration, and synchronization, reducing manual errors and enhancing operational efficiency. By leveraging SAP MDG's robust data modeling and governance features, organizations can establish a centralized repository for master data, ensuring a single source of truth. This paper discusses the architecture of SAP MDG, detailing how its automation capabilities support data profiling, cleansing, and enrichment processes. Furthermore, we analyze the impact of these automated transformations on overall data quality, compliance with regulatory standards, and decision-making processes. The findings indicate that organizations employing SAP MDG for automated data transformation experience significant improvements in data consistency, reduced time-to-market for data initiatives, and enhanced collaboration across departments. Ultimately, this research underscores the importance of automating data transformation as a critical component of effective master data management strategies, enabling organizations to navigate the complexities of modern data landscapes while fostering better business outcomes and driving growth.



Cyber Security Strategies: Protecting Digital Assets in a Rapidly Evolving Threat Landscape

December 2024

·

65 Reads

In today's digital age, cyber security has become a paramount concern for organizations as they face an ever-evolving threat landscape. Rapid technological advancements have brought about a proliferation of digital assets, from confidential business data to customer information, making them lucrative targets for cybercriminals. This paper explores advanced cyber security strategies designed to safeguard these assets against a wide array of threats, including malware, ransomware, phishing, and sophisticated hacking attempts. Traditional approaches, while still valuable, are increasingly insufficient in countering the agility and innovation displayed by cyber adversaries. Hence, a shift towards more adaptive, layered defenses is critical. We discuss a blend of proactive and reactive measures, such as employing artificial intelligence (AI) for threat detection, implementing zero-trust architectures to minimize unauthorized access, and utilizing continuous monitoring to respond to threats in real time. Additionally, strategies like multi-factor authentication, end-to-end encryption, and employee training programs are emphasized as fundamental components of a comprehensive cyber defense framework. This study further highlights the importance of regulatory compliance and risk assessment practices in identifying vulnerabilities and fortifying defenses accordingly. As cyber threats continue to grow in sophistication, adopting an integrated, dynamic approach to cyber security is essential for organizations to protect their digital assets effectively. This paper offers insights into the strategic measures that can help enterprises not only withstand but also thrive in a hostile cyber environment, thereby ensuring operational resilience and data integrity in the face of emerging risks.


SAP Billing Archiving in High-Tech Industries Compliance and Efficiency

December 2024

·

9 Reads

The increasing complexity of business processes in high-tech industries necessitates robust systems to manage vast volumes of transactional data. SAP Billing Archiving emerges as a crucial solution to address challenges in data storage, compliance, and operational efficiency. This paper explores the role of SAP Billing Archiving in high-tech industries, focusing on its ability to streamline billing processes while ensuring compliance with industry regulations. With stringent data retention laws and privacy regulations like GDPR, companies must balance efficient data management with legal and operational requirements. SAP Billing Archiving helps organizations optimize storage costs, reduce system load, and maintain accessibility to historical billing data for audit and reporting purposes. Additionally, the integration of SAP archiving solutions with existing SAP systems ensures seamless transition and minimal disruption to operations, enabling businesses to maintain efficient workflows while complying with legal mandates. The paper further discusses how SAP Billing Archiving enhances operational efficiency by automating archival processes and ensuring data integrity, thus minimizing human error and increasing process speed. Through case studies, the research highlights the practical implications and benefits of implementing SAP Billing Archiving in high-tech industries. The findings suggest that leveraging such technologies not only improves compliance with regulatory frameworks but also optimizes long-term operational efficiency, providing organizations with a competitive edge. This study underscores the importance of adopting advanced archiving solutions in navigating the dynamic landscape of high-tech industry requirements. https://www.irejournals.com/paper-details/1706407


Summary of Survey Respondents' Profiles
Current Data Governance Practices
Impact of Data Quality on Organizational Performance
Effectiveness of Data Governance Strategies
Correlation Analysis Between Data Governance Strategies and Data Quality
Data Governance Strategies In SAP Environments: Ensuring Accuracy And Consistency

December 2024

·

12 Reads

Data governance is a critical framework in SAP environments, ensuring the accuracy and consistency of data across an organization. As businesses increasingly rely on data-driven decision-making, the significance of robust governance strategies becomes paramount. This paper explores various data governance strategies tailored for SAP systems, focusing on best practices that enhance data integrity and compliance. By establishing clear data ownership, implementing standardized data management processes, and utilizing automated data validation techniques, organizations can significantly reduce discrepancies and enhance the reliability of their data assets. Furthermore, this study emphasizes the role of data stewardship in promoting a culture of accountability, where designated individuals are responsible for data quality and governance practices. The integration of advanced technologies, such as machine learning and artificial intelligence, is also discussed, showcasing how these tools can facilitate real-time monitoring and anomaly detection, thereby preemptively addressing potential data issues. Additionally, the paper highlights the importance of regular audits and compliance checks in maintaining data accuracy, ensuring adherence to industry regulations, and aligning with organizational goals. By fostering collaboration between IT and business units, organizations can create a cohesive data governance framework that supports strategic objectives. Ultimately, this research underscores that effective data governance strategies are essential for maximizing the value of data in SAP environments, leading to informed decision-making and enhanced operational efficiency.


Enhancing Laboratory Efficiency: Implementing Custom Image Analysis Tools for Streamlined Pathology Workflows

November 2024

·

5 Reads

·

5 Citations

Integrated Journal for Research in Arts and Humanities

In the field of pathology, the efficient analysis and interpretation of diagnostic images are critical for timely and accurate decision-making. Traditional manual methods for image analysis are often time-consuming, error-prone, and resource-intensive, leading to delays in diagnosis and increased workloads for pathologists. To address these challenges, this paper explores the development and implementation of custom image analysis tools to streamline pathology workflows. The integration of machine learning (ML) algorithms, computer vision techniques, and automation technologies into laboratory settings has the potential to significantly enhance the speed and accuracy of image processing tasks. This study examines how tailored image analysis solutions can optimize tasks such as tissue segmentation, feature extraction, and classification of abnormal cells. The use of such tools not only improves the diagnostic workflow but also reduces human error, enhances reproducibility, and facilitates real-time analysis. Additionally, the paper discusses the practical considerations for implementing these technologies, including software customization, integration with existing laboratory information systems, and user training. By leveraging the power of custom-built image analysis solutions, pathology laboratories can improve operational efficiency, reduce turnaround times for results, and ultimately enhance patient outcomes. The research provides insights into the future of digital pathology and offers a roadmap for laboratories looking to adopt cutting-edge technologies to stay at the forefront of diagnostic innovation.


Cross-Tabulation of Key Findings
Correlation Analysis of Key
ANOVA Analysis of Satisfaction Levels by Data Ingestion Effectiveness
Optimizing Data Ingestion and Manipulation for Sports Marketing Analytics

September 2024

·

35 Reads

·

9 Citations

In the dynamic landscape of sports marketing, the ability to effectively ingest and manipulate data is critical for driving decision-making and enhancing competitive advantage. This paper explores strategies for optimizing data ingestion and manipulation processes tailored to sports marketing analytics. We begin by analyzing the complexities of data sources, including social media, ticket sales, fan engagement metrics, and market trends. The diverse nature of these data streams necessitates robust ingestion frameworks that can accommodate real-time processing and historical data analysis. We propose a hybrid approach that leverages modern data engineering techniques, such as ETL (Extract, Transform, Load) processes, data warehousing, and cloud-based solutions. This approach enables seamless integration of structured and unstructured data, ensuring that marketers can access comprehensive insights into consumer behavior and campaign effectiveness. Furthermore, we discuss the application of advanced analytics and machine learning models to refine data manipulation techniques, enabling organizations to derive actionable insights that drive marketing strategies. By implementing these optimized processes, sports marketing professionals can enhance their understanding of audience preferences, optimize resource allocation, and ultimately improve return on investment (ROI) for marketing initiatives. This paper contributes to the existing body of knowledge by providing a framework for optimizing data ingestion and manipulation in sports marketing analytics, thus empowering organizations to make data-driven decisions that resonate with fans and stakeholders alike.


Demographics of Survey Participants
User Satisfaction with Accessibility Features
Preferred Accessibility Features
COMPREHENSIVE ANALYSIS OF ACCESSIBILITY TESTING IN FINANCIAL APPLICATIONS

September 2024

·

39 Reads

·

13 Citations

Accessibility testing in financial applications is crucial for ensuring inclusivity and compliance with legal standards, such as the Americans with Disabilities Act (ADA) and the Web Content Accessibility Guidelines (WCAG). This comprehensive analysis examines the methodologies, tools, and best practices employed in the accessibility testing of financial software. The study highlights the significance of integrating accessibility from the early stages of the software development lifecycle, emphasizing the need for continuous testing and user feedback to identify and resolve barriers faced by individuals with disabilities. Various testing techniques, including automated testing tools, manual evaluation, and user testing with diverse populations, are explored to provide a well-rounded understanding of effective strategies. Additionally, the analysis discusses common accessibility issues in financial applications, such as color contrast, keyboard navigation, and screen reader compatibility, and offers solutions to mitigate these challenges. By fostering an inclusive digital environment, financial institutions can enhance user experience, improve customer satisfaction, and ensure equitable access to services. This research aims to inform stakeholders, including developers, testers, and financial service providers, about the critical role of accessibility testing in creating user-friendly applications. The findings underscore the necessity of prioritizing accessibility as a fundamental component of financial application development, ultimately contributing to a more inclusive financial ecosystem.


Technological Innovations in Sustainable Supply Chain Planning
Challenges in Sustainable Supply Chain Implementation
Benefits of Sustainable Supply Chain Practices
Sustainability in Supply Chain Planning

August 2024

·

79 Reads

·

5 Citations

Sustainability in supply chain planning has emerged as a vital component for attaining long-term company success and environmental stewardship in today's quickly expanding global market. This is because sustainability is integral to the planning process. Sustainable supply chain planning incorporates environmental, social, and economic issues into the heart of supply chain management strategies. This is in response to the growing awareness among companies of the need to reduce their ecological imprint. When establishing a sustainable supply chain, it is necessary to conduct an exhaustive analysis of the whole supply chain lifetime, beginning with the procurement of raw materials and ending with the disposal of products at their end of life. It is necessary to put into practice procedures that cut down on waste, lessen the amount of carbon emissions, and increase the efficiency with which resources are used. The selection of suppliers who adhere to sustainable practices, the optimisation of transportation routes to minimise fuel usage, and the utilisation of technology that support the ideas of a circular economy are all important initiatives. Through the implementation of these components, organisations have the ability to reduce the risks connected with environmental requirements and interruptions in supply chain operations.


Citations (3)


... According to research by Srivastava et al. on large-scale Teradata systems, organizationsimplementing comprehensive monitoring solutions have achieved significant improvements in query performance and resource utilization. Their study reveals that effective monitoring systems in enterprise environments can process and analyze up to 850,000 concurrent queries while maintaining an average response time of 1.2 seconds, representing a 67% improvement over non-optimized systems[6].The evolution of metrics collection in Teradata environments has demonstrated remarkable capabilities in performance optimization. The research indicates that organizations leveraging advanced metric collection systems can achieve up to 75% reduction in CPU utilization through intelligent workload management and resource allocation. ...

Reference:

THE ROLE OF DATABASE RELIABILITY ENGINEERING IN ENTERPRISE INFRASTRUCTURE
Database Performance Optimization Techniques for Large-Scale Teradata Systems

Universal Research Reports

... In addition, this research highlights the importance of conducting ongoing performance reviews to suit the everevolving requirements for applications and the growing amount of storage space. After everything has been said and done, utilizing these optimization strategies not only contributes to an increase in the performance of SQL Server but also contributes to improved user experiences and an increase in the efficiency of the business [35]. ...

Improving Database Performance with SQL Server Optimization Techniques

... SQL query optimization is a major area, one of the most important strategies that one could adopt is that of indexing; which provides a great boost especially in Integrated Journal for Research in Arts and Humanities ISSN (Online): 2583-1712 Volume-1 Issue-1 || November 2021 || PP. [106][107][108][109][110][111][112][113][114][115][116] https://doi.org/10.55544/ijrah.1.1.15 situations where the application focuses on data retrieval operations. ...

Improving Digital Transformation in Enterprises Through Agile Methodologies

International Journal for Research Publication and Seminars