Master the language of modern data work with this essential reference covering 476 terms across ten core subject areas. Whether you are just entering the data profession or have years of experience, this dictionary gives you the precise vocabulary you need to work confidently across every dimension of the data landscape.
Every entry is built for practical use. Each term comes with a clear definition written for working professionals, a real workplace example showing the term in context, an explanation of why it matters in practice, the single most common mistake practitioners make, and one immediately actionable tip you can apply straight away.
Volume 1 covers the foundational layer of data work across ten chapters. Core Data Concepts establishes the essential vocabulary every data professional needs. Roles and Job Titles clarifies who does what across the modern data team. Databases and Storage covers every major storage technology from relational databases to cloud data warehouses and open table formats. SQL and Querying covers the language of data from basic queries to window functions and DAX. Data Engineering covers pipelines, orchestration, transformation frameworks, and the medallion architecture. Streaming and Real Time covers event driven systems, Apache Kafka, and real time processing patterns. Cloud and Infrastructure covers the platforms, services, and operational practices that host modern data systems. Data Architecture and Design covers the patterns and frameworks for structuring entire data platforms. Analytics and Business Intelligence covers dashboards, KPIs, self service analytics, and the full analytical method spectrum. Data Visualisation covers chart types, design principles, and the interactive features of modern BI tools.
At the back of the book you will find a complete alphabetical reference index listing all 476 terms with their chapter, category, and a one line definition for fast lookup.
This is Volume 1 of a two volume series. Volume 2 covers machine learning, deep learning and AI, statistics, MLOps, data governance, security, programming tools, and the business and soft skills that complete the data professional's vocabulary.
If you work with data in any capacity, this book belongs on your desk.
