Showing results for "Architecture" in Data Science

Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each.

Data Lake Architecture will explain how to build a useful data lake where data scientists and data analysts can solve business challenges and identify new business opportunities. Learn how to structure data lakes as well as analog, application, and text-based data ponds to provide maximum business value. Understand the role of the raw data pond and when to use an archival data pond. Leverage the four key ingredients for data lake success: metadata, integration mapping, context, and metaprocess.

In today's data-driven world, cloud storage is no longer optional—it is the backbone of modern business, government, and digital life. The Complete Guide to Modern Cloud Storage Systems delivers a clear, comprehensive exploration of how cloud storage works, why it matters, and how to design systems that are secure, scalable, and future-ready. This audiobook takes listeners deep into the architecture of modern storage environments—from foundational infrastructure and distributed systems to advanced security protocols, encryption models, redundancy strategies, and compliance frameworks.

The Complete Guide to Cloud Storage Architecture: Buckets, Permissions, and Data Access Layers The Complete Guide to Cloud Storage Architecture is a comprehensive resource designed for developers, architects, engineers, students, and IT professionals seeking a clear and practical understanding of modern cloud storage systems. This audiobook offers a structured walkthrough of every layer of cloud data storage, demystifying how today’s platforms store, organize, secure, and scale data.