Elasticsearch Data Modeling and Schema Design

The Align > Refine > Design series covers conceptual, logical, and physical data modeling (schema design and patterns) for leading technologies, combining proven data modeling practices with database-specific features to produce better applications.

Read Elasticsearch Data Modeling and Schema Design if you are a data professional who needs to expand your modeling skills to include Elasticsearch or a technologist who knows Elasticsearch but needs to grow your schema design skills.

The book’s introduction and three chapters cover the Align, Refine, and Design approach. We include what the level does in the name by rebranding Conceptual, Logical, and Physical into Align, Refine, and Design.

The introduction covers the three modeling characteristics of precise, minimal, and visual; the three model components of entities, relationships, and attributes (including keys); the three model levels of conceptual (align), logical (refine), and physical (design); and the three modeling perspectives of relational, dimensional, and query. Chapter 1, Align, is about agreeing on the common business vocabulary so everyone is aligned on terminology and general initiative scope. Chapter 2, Refine, is about capturing the business requirements. That is, refining our knowledge of the initiative to focus on what is essential. Chapter 3, Design, is about the technical requirements. That is, designing to accommodate our model’s unique software and hardware needs.

Align, Refine, and Design—that’s the approach followed in this book and reinforced through an animal shelter case study.

If you are interested in learning how to build multiple database solutions, read all the books in the Align > Refine > Design series. Since each book uses the same template, you can quickly skill up on additional database technologies.

Steve Hoberman’s first word was “data”. He has been a data modeler for over 30 years, and thousands of business and data professionals have completed his Data Modeling Master Class. Steve is the author of nine books on data modeling, including The Rosedata Stone and Data Modeling Made Simple. One of Steve’s frequent data modeling consulting assignments is to review data models using his Data Model Scorecard® technique. He is the founder of the Design Challenges group, creator of the Data Modeling Institute’s Data Modeling Certification exam, lecturer at Columbia University, and recipient of the Data Administration Management Association (DAMA) International Professional Achievement Award.

Rafid entered the Data Modeling space at the young age of 22, after completing his undergraduate degree in Biology and Mathematics from the University of Ottawa. In July 2020, he became the 10th person worldwide and first Canadian to enter the Data Modeling Institute's DMC Hall of Fame. He has experience creating and expanding standardized financial data models and data delivery mechanisms using various modeling techniques. He also has experience in the data analytics space, performing in-depth analysis of Capital Markets, Retail Banking, and Insurance data. He has worked on both relational and NoSQL data models. Rafid was a speaker at the 2021 Data Modeling Zone Europe conference, where he spoke about reverse engineering physical NoSQL data models to logical data models. In his spare time, Rafid enjoys recording music and creating digital art. Having a creative mind, he enjoys the design process and innovation associated with data modeling.