Data Engineering for Multimodal AI: Architecting Scalable Systems for Next-Generation AI Applications

Name: Data Engineering for Multimodal AI: Architecting Scalable Systems for Next-Generation AI Applications
Brand: O'Reilly Media
SKU: 9781098190781
Price: 8623.0 INR
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by Vasundra Srinivasan

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ISBN13: 9781098190781
Binding: Paperback
Subject: N/A
Publisher: O'Reilly Media
Publisher Imprint: O'Reilly Media
Publication Date: September 1, 2026
Pages: 546
Original Price: USD 79.99
Language: English
Edition: N/A
Item Weight: 862 grams
BISAC Subject(s): Data Science / Data Modeling & Design

About The Book

A shift is underway in how organizations approach data infrastructure for AI-driven transformation. As multimodal AI systems and applications become increasingly sophisticated and data hungry, data systems must evolve to meet these complex demands.

Data Engineering for Multimodal AI is one of the first practical guides for data engineers, machine learning engineers, and MLOps specialists looking to rapidly master the skills needed to build robust, scalable data infrastructures for multimodal AI systems and applications. You'll follow the entire lifecycle of AI-driven data engineering, from conceptualizing data architectures to implementing data pipelines optimized for multimodal learning in both cloud native and on-premises environments. And each chapter includes step-by-step guides and best practices for implementing key concepts.

Design and implement cloud native data architectures optimized for multimodal AI workloads
Build efficient and scalable ETL processes for preparing diverse AI training data
Implement real-time data processing pipelines for multimodal AI inference
Develop and manage feature stores that support multiple data modalities
Apply data governance and security practices specific to multimodal AI projects
Optimize data storage and retrieval for various types of multimodal ML models
Integrate data versioning and lineage tracking in multimodal AI workflows
Implement data-quality frameworks to ensure reliable outcomes across data types
Design data pipelines that support responsible AI practices in a multimodal context

About The Author

Srinivasan, Vasundra: - Vasundra Srinivasan is the Director for Solution Consulting at Salesforce, where she has spearheaded the delivery of sophisticated AI-driven customer experience strategies, leveraging advanced AI/ML pipelines across various data modalities. Her work spans key industries at the forefront of AI adoption, including fintech, telecommunications, media and entertainment, and streaming services. She has architected and implemented cutting-edge CRM, Data and AI solutions, driving digital transformation and enhancing customer experiences. Vasundra's unique blend of theoretical knowledge and practical expertise in cloud technologies, data architecture, and responsible AI practices positions her as the ideal author to guide readers through the intricate landscape of data engineering for multimodal AI systems.

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