Historical Data in Databases for AI: Structures, Preservation and Purge
Marcus Vinicius Pinto
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The past shapes the future in ways that we often overlook. In a world increasingly driven by artificial intelligence and large volumes of data, there is a type of data that carries a singular importance: historical data. They are much more than mere records of past events; They are the backbone of forecasting, analysis, and strategic decisions that drive the present and the future. In "HISTORIES ARE NOT A THING OF THE PAST: STRUCTURES, PRESERVATION, AND PURGE," you'll be guided through a fascinating universe that explores the hidden value of historical data in the digital age, offering an in-depth and thought-provoking journey into how this information is processed, preserved, and governed. This book sets out to reveal the transformative potential of historical data in building robust data architectures, fueling artificial intelligence, and offering valuable insights that can impact decisions in areas such as healthcare, finance, and education. Main Themes Covered in the Book: - The hidden power of historical data in artificial intelligence. - The evolution of databases and the processing of historical data. - Real-time temporal data storage and synchronization structures. - Temporal modeling techniques and the impact of data preservation on the performance of AI systems. - Versioning tools and the importance of informational lineage in the digital age. - Data governance as a pillar of accountability in the age of digital change. - Policies for purging and preserving historical data, including criteria for relevance and legal validity. - The balance between data purge and extensive preservation: advantages, disadvantages, and challenges. - Global regulatory compliance: GDPR, LGPD, and other relevant international regulations. - Future trends and innovations in the treatment and management of historical data. What you will achieve by reading this book: - Mastery of best practices for the processing and preservation of historical data. - Understanding of the main database architectures focused on temporal data. - Ability to apply data versioning and auditing techniques in your professional practice. - In-depth knowledge of international regulations on governance and data protection. - Tools to balance the need for data purge with the preservation of valuable information. - Strategies for dealing with scalability and performance challenges in systems that deal with historical data. - A critical and ethical view on the impact of historical data on artificial intelligence and contemporary society. Who Should Read This Book: - Professionals and experts in data science and artificial intelligence. - Data architects and software engineers. - IT managers and data governance specialists. - Academics and researchers interested in digital preservation and regulatory compliance. - Anyone who wants to understand the value of historical data and its impact on technology. Get your copy today and transform the way you view and use historical data in a digital context. With this book, you will not only understand the central role of historical data, but you will also learn how to apply it in a practical and strategic way, ensuring that the past is not only remembered, but utilized intelligently and efficiently. About the author: Marcus Pinto - Prof. Marcão - has a master's degree in Information Technology and works in the field of information architecture. IT professional with decades of experience in data intelligence has been working in the area of information technology since the mid-1980s, especially in the area of information architecture/attribute engineering, systems development and data warehouse.