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Advanced data management: For SQL, NoSQL, cloud and distributed databases

305 pages
Arcler Education Inc
Advanced data management has emerged as a crucial discipline in today's data-driven world. With the exponential growth of data and the constant evolution of technologies, organizations face complex challenges in effectively storing, retrieving, and analyzing vast amounts of information. From traditional relational databases to modern NoSQL solutions, as well as the integration of cloud and distributed architectures, advanced data management encompasses a wide array of techniques and technologies. Professionals in this field must possess a deep understanding of data modeling, query optimization, scalability, security, and the ability to navigate the complexities of managing data in diverse environments. By staying updated with the latest advancements and leveraging advanced data management techniques, organizations can harness the power of their data to gain valuable insights, improve decision-making processes, and drive innovation. “Advanced Data Management for SQL, NoSQL, Cloud, and Distributed Databases" is a comprehensive and insightful book that delves into the intricacies of managing data in the modern era. With the rapid advancement of technology, the need to effectively handle and analyze vast amounts of data has become increasingly vital. This book equips readers with the essential knowledge and skills to navigate the complexities of advanced data management. From the fundamentals of data management to exploring the relational data model, ETL processing, NoSQL databases, cloud databases, distributed database systems, and Database-as-a-Service (DBaaS), each chapter offers in-depth exploration and practical insights. Whether you are a seasoned practitioner or a newcomer to the field, this book provides a valuable resource to enhance your understanding and proficiency in managing data in SQL, NoSQL, cloud, and distributed databases.
Author Bio
Adele Kuzmiakova is a machine learning engineer working at the intersection of machine learning, computer vision, and natural language processing. Adele attended Cornell University in New York, United States for her undergraduate studies. She studied engineering with a focus on applied math. Some of the deep learning problems Adele worked on include predicting air quality from public webcams, developing a real-time human movement tracking, using 3D computer vision to create 3D avatars from selfies in order to bring online clothes shopping closer to reality, and creating visual stories and photobooks from photos on mobile devices. She is also passionate about exchanging ideas and inspiring other people and acted as a workshop organizer at Women in Data Science conference in Geneva, Switzerland in 2022 and 2023.