Uses of Generative AI for SAP HANA Data Management

Title

Uses of Generative AI for SAP HANA Data Management

Creator

Raokatta, Sivakoteswara; Akshaya, A.V.R.; Rajeswari, M. Sree; Sathiyaseelan, Vasanthaseelan

Description

This chapter examines the transformative role of generative artificial intelligence (AI) in enterprise analytics, with emphasis on the Generative Pre-trained Transformer (GPT) family and related attention-based architectures. In contrast to conventional machine-learning pipelines whose performance is constrained by task-specific supervision and rigid feature engineering generative models exploit large-scale self-supervised pre-training, enabling emergent reasoning and effective transfer across heterogeneous downstream tasks. We demonstrate these advantages through a pragmatic integration of GPT-class large language models (LLMs) within an SAP HANA environment. By fine-tuning the LLM on domain-specific SQL corpora and curated schema metadata, the system learns to synthesise syntactically correct, execution-ready SQL statements that align with the underlying business logic. This design obviates costly data-centralisation efforts: users can pose natural-language questions and obtain HANA-compliant queries over distributed enterprise data without deep knowledge of relational algebra or SAP-specific functions. Moreover, explicit injection of domain ontologies during fine-tuning improves semantic grounding and materially increases query-generation accuracy. A sales-reporting case study substantiates these claims, showing that the approach streamlines complex analytic workflows, reduces time-to-insight, and enhances report reliability. Collectively, the findings position generative AI as a catalytic technology for modernising enterprise data management and accelerating data-driven innovation. 2026 Ram Kumar Chenthur Pandian, Shanmuga Raju Sekar, Subrata Chowdhury, Muhammad Rukunuddin Ghalib, and Kassian T.T. Amesho.

Source

Artificial Intelligence in Detecting Autism;pp.237-246

Date

01-01-2026

Publisher

CRC Press

Coverage

Raokatta S., Singapore Institute of Technology, Singapore; Akshaya A.V.R., School of Business and Management, CHRIST University, Bengaluru, India; Rajeswari M.S., Department of Computer Science and Engineering, Jeppiaar Institute of Technology, Chennai, India; Sathiyaseelan V., Department of Autotronics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil N?du, 602105, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 978-104053668-1; 978-103286653-6;

Format

online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1201/9781003541318-23

https://www.scopus.com/pages/publications/105037439465?origin=resultslist