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Metadata Recycling into Graph Data Models

The Guide to Data Model Recycling using Neo4j

Recycle, Reuse and Reduce also for data models! Why waste time remodeling the same data, just because you go to graph? Learn how to auto-generate graph data models (for Neo4j) from legacy data models in UML, XML, ERD, concept maps and other formats. Missing something on the list? Let the author know!

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About

About

About the Book

What if the database died some years ago, but you still have an old UML or XML file with the model in it. And you need to model the same domain for graph data bases? This is one of the scenarios this book intends to help you with.

There are 70+ ERD-supporting tools and 50+ UML tools, many of which are also used for data modeling. That translates to a lot of data models. Can they be "recycled", also in agile projects? There must be hundreds of thousands of good, reusable data models! Why waste such a large resource of business metadata?

Much similar to data science we have a need to (call it "Metadata Science") read, transform, scope / reduce / enhance and adapt data models to modern database technologies. Not least graph databases, if you ask me.

This book explains how to do that. Cypher®-scripts are included for Concept Maps (CmapTools®), CSDL, XML Schemas, StarUML v1 and UML® via various XMI® formats. The most recent addition is FileMaker® data models.

The book also explains how to optionallay build a simple graph-based metadata repository, which has full lineage back to the source data model, and it supports identities, uniqueness, mandatory fields and basic datatypes.

Cypher-scripts for repository handling are indeed also part of the book (under a MIT license).

We suggest a choice of two approaches:

  • Fast Track Data Models (agile)
  • Super Data Models (crafted, using the repository.

Looking for a graph database modeling tool? Now, everything you need for recycling of data models is available inside this book. 50+ scripts (and growing) plus the repository model providing data lineage.

Any inquiries about this book and the scripts can be sent to @VizDataModeler (info at graphdatamodeling dot com).

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Author

About the Author

Thomas Frisendal

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

Visual Design of GraphQL Data, first on Leanpub then on Apress 2018

He is blogging at Dataversity.

Thomas lives in Copenhagen, close to the Airport.

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