Technics Publications

Data Cataloging

Original price was: $64.95.Current price is: $59.95.

Data Cataloging: Embracing Artificial Intelligence and Machine Learning for Metadata, by Jeff Harris

Manage and optimize metadata using Artificial Intelligence (AI) and Machine Learning (ML) through this comprehensive guide on the intricate and pivotal world of data cataloging.  


Part I: Data Cataloging Introduction

Chapter 1: Understanding Data Cataloging

Part II: Foundations of Data Cataloging

Chapter 2: Data Cataloging Principles

Chapter 3: Types of Data Catalogs

Chapter 4: Data Cataloging Architecture

Part III: Building an Effective Data Catalog

Chapter 5: Data Profiling and Data Discovery

Chapter 6: Data Cataloging Best Practices

Chapter 7: Data Cataloging Tools and Technologies

Part IV: Implementing and Maintaining a Data Catalog

Chapter 8: Data Cataloging Strategy and Planning

Chapter 9: Data Cataloging Implementation

Chapter 10: Metadata Harvesting and Automation

Chapter 11: Data Cataloging for Big Data and Streaming Data

Part V: Utilizing the Data Catalog

Chapter 12: Data Catalog for Data Consumers

Chapter 13: Data Catalog for Data Governance and Compliance

Chapter 14: Data Catalog for Business Intelligence

Part VI: Future Trends in Data Cataloging

Chapter 15: Artificial Intelligence in Data Cataloging

Chapter 16: Blockchain and Data Cataloging

Chapter 17: Data Catalogs of Tomorrow

Part VII: Case Studies in Data Cataloging Implementation

Chapter 18: Case Studies

Manage and optimize metadata using Artificial Intelligence (AI) and Machine Learning (ML) through this comprehensive guide on the intricate and pivotal world of data cataloging.

The book demystifies the concepts of data cataloging, highlighting its critical role in ensuring that data within organizations is accurate, accessible, and actionable. Jeff meticulously lays out strategies and insights on creating a robust data catalog that manages metadata and uses AI and ML to enhance its usability and reliability.

In an era dominated by data-driven decisions, understanding and implementing effective data cataloging has become paramount for businesses and organizations across the globe. Jeff navigates through the complexities of data cataloging, providing readers with practical insights, actionable strategies, and a thorough understanding of utilizing AI and ML to enhance metadata management. The book is a doorway to understanding and implementing a fundamental component that ensures the reliability and accessibility of your data, enabling informed decision-making and data-driven strategies.

This book is for data professionals, IT experts, business analysts, and organizational leaders who need a foundational and advanced understanding of data cataloging. Through real-world examples, case studies, and a step-by-step guide on implementing the concepts discussed, Jeff ensures that the reader gains the knowledge and tools needed to navigate the complexities of data cataloging. His insights on leveraging AI and ML for metadata management provide a futuristic perspective and offer practical strategies that organizations can implement to enhance their data management practices.

By embracing the book’s principles, you can navigate the vast and often confusing world of data management with clarity and precision. This book will guide you through creating, managing, and optimizing a data catalog that serves as the backbone of your data management strategy. This book is an investment towards understanding, implementing, and mastering data cataloging, ensuring that your data is not merely stored but is optimized, reliable, and ready to drive your strategic initiatives forward.

For anyone seeking to harness the power of their data, ensure its reliability, and utilize it to drive informed decisions and strategies, this indispensable guide will navigate you through the complexities and opportunities present in the world of data cataloging, ensuring that you are well-equipped to create a robust, reliable, and optimized data management strategy.

About Jeff

Jeff Harris holds the esteemed Director of Data Architecture position at a renowned non-profit organization within the education sphere. His illustrious three-decade tenure in the IT arena has been punctuated by a deep specialization in Data Modeling and Data Architecture, honed over two decades.


Throughout his career, Mr. Harris has navigated high-stakes projects with major corporate entities, diligently orchestrating the integration of erwin and its allied products. He is adept at crafting erwin APIs and applying sophisticated data modeling methodologies and frameworks. His projects carry an international imprint, reaching shores from South Africa and New Zealand to Europe, the UK, and the USA. Such endeavors have garnered accolades from a varied clientele spanning the banking, government, logistics, retail, freight, and petroleum sectors.


Beyond his extensive project work, Mr. Harris’s prowess shines in the design of Data Lakehouses, Data Warehouses, and Operational Data Stores, as well as in sculpting comprehensive Enterprise Data Architectures. His profound acumen has birthed numerous influential publications on data-centric matters. His deftness with the erwin Data Modeler toolset, spanning from version 3.5 to its contemporary iterations, ensures that he consistently delivers best-in-class solutions and invaluable expertise to his clientele.


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