Triple

Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).

Phrase: Big Data: Principles and best practices of scalable realtime data systems | Statement: [Nathan Marz, authorOf, Big Data: Principles and best practices of scalable realtime data systems]

Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"

Entity: Big Data: Principles and best practices of scalable realtime data systems
Triple: [Nathan Marz, authorOf, Big Data: Principles and best practices of scalable realtime data systems]

"Big Data: Principles and Best Practices of Scalable Realtime Data Systems" is a technical book that explains architectural patterns and practical techniques for building large-scale, fault-tolerant, real-time data processing systems.