Visual Design of GraphQL Data
Last updated on 2018-04-27
About the Book
Understand and Visualize GraphQL, Prettify Legacy Content and get the API Structures Right!
New in the April 2018 version: Issues with legacy data as well as issues and benefits in combining GraphQL with Neo4j graph databases.
GraphQL is indeed an attractive data API for applications (and people). The GraphQL Schema is pivotal to the success of a GraphQL API in that it describes an application side scope as well as the mapping to data sources.
There are many contexts, where complex structures and semantics must be communicated effectively, and the trick invariably turns out to be: Use good visualizations! Most development projects involve many stakeholders.
The main proposition of this book is graph visualization: GraphQL Schema structure and meaning must be visualized, and the book shows you how. Since the schema is a “data graph” containing related concepts in a network organized as a directed graph, the increasingly popular property graph paradigm is very appropriate for visualizing GraphQL structures and semantics.
The second theme of this book is that of quality of the content. GraphQL APIs can be used in many constellations possibly including legacy data and/or externally sourced data. Quality must be ensured in all cases. The book contains simple guidelines based on lessons learned from real life data discovery and unification. This helps developers and architects to get good quality in the resulting API designs. And the visual techniques help in producing convincing visual communication about the structure of the API designs.
The third theme is how to handle GraphQL with legacy data as well as with Neo4j graph databases.
Spending time on schema quality means that developers work from sharp definitions, which in turn leads to greater productivity and well-structured applications.
About the Author
Thomas Frisendal is an experienced data guy with more than 30 years on the IT vendor side and as an independent consultant. He has worked with databases and data modeling since the late 70s; since 1995 primarily on data warehouse projects. He has a strong urge to visualize everything as graphs - even datamodels! He excels in the art of turning data into information and knowledge. His approach to information-driven analysis and design is "New Nordic" in the sense that it represents the traditional Nordic values such as superior quality, functionality, reliability and innovation by new ways of communicating the structure and meaning of the business context.
Thomas is an active writer and speaker.
He has previously published:
Design Thinking Business Analysis: Business Concept Mapping Applied, Springer, 2012 and
Graph Data Modeling for NoSQL and SQL: Visualize Structure and Meaning, Technics Publications, 2017
He is blogging at Dataversity.
Thomas lives in Copenhagen, close to the Airport.
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