MarkLogic Data Modeling and Schema Design

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$59.95

The Align > Refine > Design Series, by Steve Hoberman and industry experts

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.

Topics

Chapter 1: About Database Models

Relational

Key-value

Wide column

Graph

RDF graph

Property graph

Document

A note about terminology

Data types


Chapter 2: About MarkLogic

Multi-model features of MarkLogic

Does data modeling matter in MarkLogic?

Storage model

Document URI

Document organization

Directories

Collections


Chapter 3: The JSON Document Model

Polymorphism

Fields with multiple data types

Multiple document types in a JSON collection

Schema evolution and versioning


Chapter 4: About Data Models

Data model explanation

Three model characteristics

Precise

Minimal

Visuals

Three model components

Entities

Relationships

Attributes and keys

Three model levels

Business terms (Align)

Logical (Refine)

Domain-Driven Data Modeling

Physical (Design)

Three model perspectives

Relational

Dimensional

Query


Chapter 5: Align

Purpose

Our animal shelter

Approach

Step 1: Ask the six strategic questions

Step 2: Identify and define the terms

Step 3: Capture the relationships

Step 4: Determine the visual

Step 5: Review and confirm

Three tips

Three takeaways


Chapter 6: Refine

Purpose

Approach

Step 1: Apply elicitation techniques

Measure Connections

Step 2: Analyze Usage Patterns

Step 3: Refine Queries

Three tips

Three takeaways


Chapter 7: Design

Purpose

Approach

Step 1: Select database(s)

Step 2: Add secret sauce

MarkLogic schema design principles

Embedding versus referencing

Embedding

Referencing

Rules for embedding and referencing

Schema design patterns

The Approximation Pattern

The Attribute Pattern

The Bucket Pattern

The Computed Pattern

The Document Versioning Pattern

The Envelope Pattern

The Extended Reference Pattern

The Polymorphic Pattern

The Schema Versioning Pattern

The Subset Pattern

The Semantic Graph Pattern

Primary keys

Monitoring schema evolution

Schema migration

Step 3: Optimize

Indexing

Generation of test data

Four tips

Three takeaways

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

We 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.  Align is about agreeing on the common business vocabulary so everyone is aligned on terminology and general initiative scope. Refine is about capturing the business requirements. That is, refining our knowledge of the initiative to focus on what is essential.  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.

About Steve

Steve Hoberman is a world-recognized innovator and thought-leader in the field of data modeling. He has worked as a business intelligence and data management practitioner and trainer since 1990. He is the author of Data Modelers Workbench and Data Modeling Made Simple, the founder of the Design Challenges group and the inventor of the Data Model Scorecard®.

About Sandy

Sandy Davis is an Enterprise Data Architect at a major Class 1 railroad in the United States.  Sandy has been working with Relational (SQL) and NoSQL databases in the roles of developer, database administrator, and data modeler/designer since 1989.  Sandy has been leading the deployment and adoption of MarkLogic since 2018. Several mission-critical railroad operational applications use MarkLogic.

About Biju

Biju George is a seasoned professional with over 25 years of progressive experience catering to the critical technology needs of enterprise customers across various industries such as insurance, healthcare, finance, and logistics. As a Sales and Solutions Engineer, Biju specializes in working with large enterprises, leveraging his expertise to resolve complex data problems using MarkLogic, the leading enterprise-hardened schema-agnostic database platform in the global market. Biju has been working with MarkLogic since 2018.

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