Freestyle Fridays - The Skills Gap in Data

This book is a definitive guide to dimensional modeling, starting with fundamental design recommendations and progressing through increasingly complex real-world scenarios. It covers advanced dimensional modeling patterns, including bridge tables, multivalued attributes, and slowly changing dimensions. The book also includes case studies from various industries such as retail sales, financial services, telecommunications, and healthcare. It emphasizes the use of the bus matrix for identifying relationships between dimensions and applications and provides guidance on ETL systems and the Kimball BI/DW life cycle methodology.

This book is a classic in the data warehousing industry, covering the fundamentals of data warehouse systems as well as new topics like methods for handling unstructured data, storing data across multiple storage media, and the pros and cons of relational versus multidimensional design. It also discusses advanced topics including data monitoring, testing, and measuring return on investment in data warehouse projects. The book is designed for both technologists and end users, providing a thorough look at data warehousing from various perspectives[1][3][4].

This book guides developers through the essential concepts of modern database and storage engine internals. It explores storage classification and taxonomy, including B-Tree-based and immutable Log Structured storage engines. The book also delves into how database files are organized, using auxiliary data structures such as Page Cache, Buffer Pool, and Write-Ahead Log. Additionally, it covers distributed systems, explaining how nodes and processes connect and build complex communication patterns, and discusses consistency models and how distributed storage systems achieve consistency. The book draws from numerous books, papers, blog posts, and the source code of several open source databases to provide a comprehensive understanding of database internals.

This book helps software engineers and architects understand the pros and cons of various technologies for storing and processing data. It covers fundamental principles, trade-offs, and design decisions in data systems, including scalability, consistency, reliability, efficiency, and maintainability. The book delves into distributed systems research, the architecture of data systems, and how to make informed decisions about different tools and technologies. It does not provide detailed instructions on specific software packages but focuses on the underlying principles and trade-offs essential for designing data-intensive applications[2][4][5].