By Steve Hoberman
Now, what when you had a time computing device and will return and skim this ebook. you are going to examine that even NoSQL databases like MongoDB require a few point of knowledge modeling.
Data modeling is the method of studying concerning the info, and despite know-how, this method has to be played for a winning application. you will study the worth of conceptual, logical, and actual info modeling and the way each one level raises our wisdom of the knowledge and decreases assumptions and negative layout decisions.
Read this e-book to benefit how you can do info modeling for MongoDB purposes, and achieve those 5 objectives:
- Understand how info modeling contributes to the method of studying concerning the info, and is, consequently, a required approach, even if the ensuing database isn't relational. that's, NoSQL doesn't suggest NoDataModeling!
- Know how NoSQL databases range from conventional relational databases, and the place MongoDB fits.
- Explore every one MongoDB item and understand how each one compares to their info modeling and conventional relational database opposite numbers, and research the fundamentals of including, querying, updating, and deleting information in MongoDB.
- Practice a streamlined, template-driven method of appearing conceptual, logical, and actual information modeling. realize that info modeling doesn't continually need to bring about conventional facts models!
- Distinguish top-down from bottom-up improvement ways and whole a top-down case research which ties the entire modeling thoughts together.
This publication is written for someone who's operating with, or might be operating with MongoDB, together with enterprise analysts, info modelers, database directors, builders, undertaking managers, and knowledge scientists. There are 3 sections:
- In part I, Getting Started, we are going to demonstrate the facility of knowledge modeling and the tight connections to facts types that exist whilst designing any kind of database (Chapter 1), examine NoSQL with conventional relational databases and the place MongoDB suits (Chapter 2), discover every one MongoDB item and understand how each one compares to their facts modeling and standard relational database opposite numbers (Chapter 3), and clarify the fundamentals of including, querying, updating, and deleting information in MongoDB (Chapter 4).
- In part II, Levels of Granularity, we hide Conceptual facts Modeling (Chapter 5), Logical facts Modeling (Chapter 6), and actual facts Modeling (Chapter 7). become aware of the "ing" on the finish of every of those chapters. We specialize in the method of creating each one of those versions, that is the place we achieve crucial enterprise knowledge.
- In part III, Case Study, we'll clarify either most sensible down and backside up improvement ways and struggle through a most sensible down case learn the place we commence with company specifications and finish with the MongoDB database. this situation learn will tie jointly all the ideas within the past seven chapters.
Nike Senior info Architect Ryan Smith wrote the foreword. Key issues are incorporated on the finish of every bankruptcy with the intention to strengthen options. moreover, this e-book is loaded with hands-on workouts, besides their solutions supplied in App A. App B includes all the book’s references and App C the
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Data Modeling for MongoDB: Building Well-Designed and Supportable MongoDB Databases by Steve Hoberman