AI-Driven Data Engineering
Chuck Sherman
In this age of data, where information is being generated at an unprecedented rate, the role of data engineering has become more critical than ever. Data engineers are the unsung heroes who work behind the scenes to ensure that data is collected,...
Location:
United States
Description:
In this age of data, where information is being generated at an unprecedented rate, the role of data engineering has become more critical than ever. Data engineers are the unsung heroes who work behind the scenes to ensure that data is collected, stored, transformed, and made accessible for analysis. However, with the advent of artificial intelligence (AI), the landscape of data engineering is undergoing a profound transformation. This book, "AI-Driven Data Engineering" explores the convergence of AI and data engineering. It delves into the foundations of data engineering, the rise of AI, and how AI is reshaping every aspect of the data engineering pipeline. Through real-world case studies, practical insights, and ethical considerations, this book equips readers with the knowledge and skills needed to thrive in the AI-driven data engineering landscape. Whether you are a data engineer looking to stay ahead of the curve, a data scientist interested in the data preparation process, or a business leader seeking to harness the power of AI and data, this book offers a comprehensive guide to the exciting world of AI-driven data engineering. Let's embark on this journey together and discover how AI is revolutionizing the way we engineer and harness the power of data for a brighter and more data-driven future. Duration - 11h 58m. Author - Chuck Sherman. Narrator - Ray Collins. Published Date - Thursday, 08 January 2026. Copyright - © 2025 Khin Soe ©.
Language:
English
Opening Credits
Duration:00:00:12
Chapter 1 the data revolution
Duration:00:10:40
Chapter 2 foundations of data
Duration:00:20:18
Chapter 3 the rise of artificial
Duration:00:52:44
Chapter 4 ai driven data ingestion
Duration:00:11:06
Chapter 5 ai enhanced data storage
Duration:00:22:06
Chapter 6 intelligent data
Duration:00:15:43
Chapter 7 seamless data integration with
Duration:00:31:12
Chapter 8 ensuring data quality through
Duration:00:20:27
Chapter 9 ai driven data pipelines
Duration:00:18:32
Chapter 10 case studies in ai driven
Duration:00:14:05
Chapter 11 challenges and ethical
Duration:00:15:17
Chapter 12 the future of data
Duration:00:14:40
Opening credits
Duration:00:00:11
Chapter 1 understanding real time data
Duration:00:13:39
Chapter 2 use cases for real time data
Duration:00:22:38
Chapter 3 challenges in real time data
Duration:00:28:33
Chapter 4 architectures for real time
Duration:00:18:00
Chapter 5 tools and technologies
Duration:00:29:56
Chapter 6 data ingestion and collection
Duration:00:12:08
Chapter 7 data processing and
Duration:00:13:16
Chapter 8 data storage and persistence
Duration:00:22:28
Chapter 9 monitoring and management
Duration:00:20:34
Chapter 10 real time analytics and
Duration:00:17:27
Chapter 11 security and compliance
Duration:00:16:14
Chapter 12 building scalable and
Duration:00:16:58
Chapter 13 future trends in real time
Duration:00:16:01
Chapter 1 introduction to serverless
Duration:00:13:42
Chapter 2 fundamentals of serverless
Duration:00:11:59
Chapter 3 data sources and ingestion
Duration:00:13:46
Chapter 4 data transformation with
Duration:00:13:31
Chapter 5 serverless data storage
Duration:00:12:31
Chapter 6 serverless data orchestration
Duration:00:12:46
Chapter 7 data quality and governance
Duration:00:11:16
Chapter 8 monitoring, logging, and error
Duration:00:09:35
Chapter 9 scalability and performance
Duration:00:15:24
Chapter 10 case studies in serverless
Duration:00:10:32
Chapter 11 future trends and innovations
Duration:00:12:33
Chapter 12 getting started with
Duration:00:32:25
Chapter 13 challenges and pitfalls
Duration:00:25:27
Chapter 14 building a serverless data
Duration:00:27:51
Ending Credits
Duration:00:00:07