Sibaram Prasad Panda
Biography
I currently serve as the Senior Vice President, Data and Analytics at Decision Ready Solutions, where I lead global initiatives in data architecture, big data analytics, data engineering, and data warehousing for clients in the Financial, Banking and Mortgage Servicing sectors. My work centers on architecting SaaS-based products, designing scalable cloud-native solutions, and delivering data-driven insights through advanced analytics platforms.
With deep expertise in Azure Fabrics, Data Factory, Databricks, ADLS, and Power BI, I have led enterprise-grade data warehouse and analytics implementations. My responsibilities extend to ensuring operational excellence and business continuity across production systems. I also oversee cloud migration strategies, leveraging hybrid architectures to modernize legacy workloads and optimize performance.
I have actively implemented a range of Cybersecurity practices and AI-driven monitoring tools to safeguard the product ecosystem. This includes performing regular security audits, enforcing data protection policies, configuring automated alerts for potential threats, and ensuring adherence to compliance frameworks such as the Gramm-Leach-Bliley Act (GLBA) and Sarbanes-Oxley (SOX) Act. My goal is to create a proactive, resilient security posture across all enterprise systems while integrating AI-enabled mechanisms for faster threat detection and incident response.
My experience spans Snowflake data architecture, data modeling, ETL development, and DevOps practices on Azure, along with Agile/Scrum methodologies. I have designed strategic roadmaps for enterprise data platforms and implemented the best practices for data migration between on-prem and cloud environments. In earlier roles, I served as a Database Architect and Administrator, managing high-availability SQL Server environments using Availability Groups, clustering, replication, and PowerShell scripting.
I have led diverse technical teams, including a 10-member senior DBA group supporting a Fortune 500 client, and have been responsible for Tier-3 production support, incident/problem management, and ITIL-aligned operational processes. My career reflects a strong blend of technical leadership, cybersecurity governance, and AI-enabled innovation, empowering organizations to harness the full value of their data assets while operating securely and in compliance.
Research Interest
Experienced Research Engineer with an extensive background in engineering principles, project leadership, and the effective application of research in technological companies. Bringing forth extensive experience in performing research on product development processes and offering solutions and alterations to improve safety and effectiveness. Adept in working with engineers and project managers at multiple levels to utilize research data effectively and achieve optimal results.
Published over 20 peer-reviewed research papers in artificial intelligence, cloud computing, cybersecurity, and data analytics, with a focus on applied innovation and cross-disciplinary impact. Several papers are published in IEEE journals and conferences.
? Authored three academic books:
1. Artificial Intelligence Across Borders: Transforming Industries Through Intelligent Innovation ? examining global AI adoption and real-world applications.
2. Mastering Azure Fabric: Unified Data Engineering, Governance, and Artificial Intelligence in the Cloud ? published by Deep Science Publishing.
3. Relational, NoSQL, and Artificial Intelligence-Integrated Database Architectures: Foundations, Cloud Platforms, and Regulatory-Compliant Systems ? addressing modern data architectures and regulatory compliance.
? Peer-reviewed multiple research papers for leading international journals and conferences, contributing to the advancement of high-quality scientific scholarship.
? Authored thought leadership articles and technical blogs on Medium, simplifying complex research for practitioners, academics, and the broader tech audience.
Abstract
AI-Powered Databases: Transforming Query Optimization, Security, and Data Intelligence
The convergence of artificial intelligence (AI) and database technologies is significantly altering how modern enterprises manage, secure, access, and analyze data. This presentation explores the profound impact of AI on database systems, with particular focus on developments in intelligent query optimization, anomaly detection, access control, and predictive analytics. AI improves security and privacy through behavior-based intrusion detection and automated threat response in distributed settings.
We review the development of AI-assisted database engines, focusing on machine learning in query planning, indexing, and workload forecasting. We also discuss how AI improves security and privacy through behavior-based intrusion detection and automated threat response in distributed settings.
Case studies from cloud-native platforms such as Snowflake, Microsoft Fabric, and Amazon Redshift will demonstrate the use of AI in large-scale performance management. The presentation will provide information on applying reinforcement learning for dynamic optimization, NLP models for semantic query translation, and deep learning techniques for data classification and anomaly detection.
