PARTICULAR
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Page No.
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Generative AI in Enterprise Software Testing
Prasad Banala
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1-6
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Digital Experience Observability in AI-Enhanced Systems: A Framework for Product Managers
Tingting Lin
Abstract:
This research addressed a critical gap in measuring AI system effectiveness within enterprise environments, with a specific focus on incident management applications.
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6-14
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RAG - Game Changer in GenAI Space
Shekhar Jha
Abstract:
Generative AI Challenge - AI hallucinations
It is challenging to rely on Generative AI (GenAI) to provide users and customers with custom, correct and real-time answers to their questions
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14-37
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Optimizing Data Lakehouse Architectures for Scalability and Performance
Pratap Pachipulusu
Abstract:
As organizations increasingly rely on data-driven decision-making, the need for efficient, scalable, and high-performing data architectures has grown significantly.
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38-42
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AI-Driven Automation in Data Engineering: Opportunities and Challenges
Gowtham Kumar Reddy Mittoor
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43-47
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A Deep Learning Framework for High-Dimensional Data Analytics
Hanza Parayil Salim
Abstract:
High-dimensional data analysis has become an essential area of focus across various fields, including healthcare, finance, cybersecurity, and scientific research.
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48-54
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The Evolution of Data Pipelines: From Batch Processing to Real-Time Streaming
Greeshma Suryadevara
Abstract:
Data pipelines form the backbone of modern data engineering, facilitating the extraction, transformation, and loading (ETL) of data to support analytics and decision-making.
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55-59
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The Future of Data Engineering: Trends in Data Mesh and Decentralized Data Architectures
Greeshma Suryadevara
Abstract:
As organizations scale their data ecosystems, traditional centralized data architectures struggle to keep up with the demands of modern analytics, governance, and scalability.
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60-65
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Data Governance and Compliance in Large-Scale Data Engineering
Suresh Putteti
Abstract:
With the increasing volume, velocity, and variety of data being generated across industries, the role of data governance and compliance has become critical in ensuring data integrity, security, and regulatory adherence.
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66-71
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Data Quality and Governance: Examine strategies for maintaining data quality, integrity, and governance in large-scale data environments
Harsha Kamma
Abstract:
In today’s world, data is often referred to as the new oil, driving decision-making and innovation across industries.
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72-81
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Hypercare Post Go-Live Support for SAP Projects
Krishna Chaitanya Reddy Katakam
Abstract:
This article is aimed to provide a structured approach for managing effective support of SAP systems, during hypercare after Go-Live. Activities, priority of tickets, SLAs and support groups are defined in this document.
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81-87
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Tokenization Impact on the Payment Industry: Security, Regulatory, and Adoption
Kunal Nandi
Abstract:
In the payment ecosystem, traditional payment methods (i.e., card transactions) expose sensitive card details like card numbers, CVV2, and expiry dates to merchants and thirdparty apps (for internet transactions) while performing digital transactions.
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88-94
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Streamlining Data Loading in Python: A Guide for Beginners
Gajula Lokesh Kumar
Abstract:
In today's data-driven world, efficiently loading and managing various data sources is a crucial skill for aspiring data scientists and software developers.
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95-101
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