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Mongodb Data Modeling


Mongodb Data Modeling
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Data Modeling For Mongodb


Data Modeling For Mongodb
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Author : Steve Hoberman
language : en
Publisher: Technics Publications
Release Date : 2014-06-01

Data Modeling For Mongodb written by Steve Hoberman and has been published by Technics Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-01 with Computers categories.


Congratulations! You completed the MongoDB application within the given tight timeframe and there is a party to celebrate your application’s release into production. Although people are congratulating you at the celebration, you are feeling some uneasiness inside. To complete the project on time required making a lot of assumptions about the data, such as what terms meant and how calculations are derived. In addition, the poor documentation about the application will be of limited use to the support team, and not investigating all of the inherent rules in the data may eventually lead to poorly-performing structures in the not-so-distant future. Now, what if you had a time machine and could go back and read this book. You would learn that even NoSQL databases like MongoDB require some level of data modeling. Data modeling is the process of learning about the data, and regardless of technology, this process must be performed for a successful application. You would learn the value of conceptual, logical, and physical data modeling and how each stage increases our knowledge of the data and reduces assumptions and poor design decisions. Read this book to learn how to do data modeling for MongoDB applications, and accomplish these five objectives: Understand how data modeling contributes to the process of learning about the data, and is, therefore, a required technique, even when the resulting database is not relational. That is, NoSQL does not mean NoDataModeling! Know how NoSQL databases differ from traditional relational databases, and where MongoDB fits. Explore each MongoDB object and comprehend how each compares to their data modeling and traditional relational database counterparts, and learn the basics of adding, querying, updating, and deleting data in MongoDB. Practice a streamlined, template-driven approach to performing conceptual, logical, and physical data modeling. Recognize that data modeling does not always have to lead to traditional data models! Distinguish top-down from bottom-up development approaches and complete a top-down case study which ties all of the modeling techniques together. This book is written for anyone who is working with, or will be working with MongoDB, including business analysts, data modelers, database administrators, developers, project managers, and data scientists. There are three sections: In Section I, Getting Started, we will reveal the power of data modeling and the tight connections to data models that exist when designing any type of database (Chapter 1), compare NoSQL with traditional relational databases and where MongoDB fits (Chapter 2), explore each MongoDB object and comprehend how each compares to their data modeling and traditional relational database counterparts (Chapter 3), and explain the basics of adding, querying, updating, and deleting data in MongoDB (Chapter 4). In Section II, Levels of Granularity, we cover Conceptual Data Modeling (Chapter 5), Logical Data Modeling (Chapter 6), and Physical Data Modeling (Chapter 7). Notice the “ing” at the end of each of these chapters. We focus on the process of building each of these models, which is where we gain essential business knowledge. In Section III, Case Study, we will explain both top down and bottom up development approaches and go through a top down case study where we start with business requirements and end with the MongoDB database. This case study will tie together all of the techniques in the previous seven chapters. Nike Senior Data Architect Ryan Smith wrote the foreword. Key points are included at the end of each chapter as a way to reinforce concepts. In addition, this book is loaded with hands-on exercises, along with their answers provided in Appendix A. Appendix B contains all of the book’s references and Appendix C contains a glossary of the terms used throughout the text.



Mongodb Recipes


Mongodb Recipes
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Author : Subhashini Chellappan
language : en
Publisher: Apress
Release Date : 2019-12-13

Mongodb Recipes written by Subhashini Chellappan and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-13 with Computers categories.


Get the most out of MongoDB using a problem-solution approach. This book starts with recipes on the MongoDB query language, including how to query various data structures stored within documents. These self-contained code examples allow you to solve your MongoDB problems without fuss. MongoDB Recipes describes how to use advanced querying in MongoDB, such as indexing and the aggregation framework. It demonstrates how to use the Compass function, a GUI client interacting with MongoDB, and how to apply data modeling to your MongoDB application. You’ll see recipes on the latest features of MongoDB 4 allowing you to manage data in an efficient manner using MongoDB. What You Will Learn Work with the MongoDB document model Design MongoDB schemas Use the MongoDB query language Harness the aggregation framework Create replica sets and sharding in MongoDB Who This Book Is ForDevelopers and professionals who work with MongoDB.



Mongodb Data Modeling And Schema Design


Mongodb Data Modeling And Schema Design
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Author : Daniel Coupal
language : en
Publisher:
Release Date : 2023-05-24

Mongodb Data Modeling And Schema Design written by Daniel Coupal and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-24 with categories.


Each book in the Align > Refine > Design series covers conceptual, logical, and physical data modeling (schema design) for a specific database product, combining the best of data modeling practices with solution-specific considerations, which lead to effective communication tools and extensible datastore foundations. Read MongoDB Data Modeling and Schema Design if you are a data architect or modeler who needs to expand your modeling skills to include MongoDB, or if you are a database administrator or developer who knows MongoDB but needs to expand your schema design skills. The book's introduction and three chapters cover the proven approach. The introduction covers the three modeling characteristics of precise, minimal, and visual; the three model components of entities, relationships, and attributes; the three model levels of conceptual (align), logical (refine), and physical (design); the three modeling perspectives of relational, dimensional, and NoSQL; and the three modeling challenges with NoSQL (tactical, strategy, and cultural). Next, Chapter 1 covers Align, Chapter 2 Refine, and Chapter 3 Design. An animal shelter case study creates continuity across these three modeling levels. 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 is created from the same template, once you read one, you'll be able to pick up the techniques for another database solution quickly.



Mongodb Data Modeling


Mongodb Data Modeling
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Author : Wilson Da Rocha Franca
language : en
Publisher:
Release Date : 2015

Mongodb Data Modeling written by Wilson Da Rocha Franca and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computers categories.


This book is intended for database professionals, software developers, and architects who have some previous experience with MongoDB and now want to shift their focus to the concepts of data modeling. If you wish to develop better schema designs for MongoDB-based applications, this book is ideal for you.



Hands On Big Data Modeling


Hands On Big Data Modeling
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Author : James Lee
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-30

Hands On Big Data Modeling written by James Lee and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with Computers categories.


Solve all big data problems by learning how to create efficient data models Key FeaturesCreate effective models that get the most out of big dataApply your knowledge to datasets from Twitter and weather data to learn big dataTackle different data modeling challenges with expert techniques presented in this bookBook Description Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements. To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently. What you will learnGet insights into big data and discover various data modelsExplore conceptual, logical, and big data modelsUnderstand how to model data containing different file typesRun through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modelingCreate data models such as Graph Data and Vector SpaceModel structured and unstructured data using Python and RWho this book is for This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.



Data Model Scorecard


Data Model Scorecard
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Author : Steve Hoberman
language : en
Publisher: Technics Publications
Release Date : 2015-11-01

Data Model Scorecard written by Steve Hoberman and has been published by Technics Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-01 with Computers categories.


Data models are the main medium used to communicate data requirements from business to IT, and within IT from analysts, modelers, and architects, to database designers and developers. Therefore it’s essential to get the data model right. But how do you determine right? That’s where the Data Model Scorecard® comes in. The Data Model Scorecard is a data model quality scoring tool containing ten categories aimed at improving the quality of your organization’s data models. Many of my consulting assignments are dedicated to applying the Data Model Scorecard to my client’s data models – I will show you how to apply the Scorecard in this book. This book, written for people who build, use, or review data models, contains the Data Model Scorecard template and an explanation along with many examples of each of the ten Scorecard categories. There are three sections: In Section I, Data Modeling and the Need for Validation, receive a short data modeling primer in Chapter 1, understand why it is important to get the data model right in Chapter 2, and learn about the Data Model Scorecard in Chapter 3. In Section II, Data Model Scorecard Categories, we will explain each of the ten categories of the Data Model Scorecard. There are ten chapters in this section, each chapter dedicated to a specific Scorecard category: · Chapter 4: Correctness · Chapter 5: Completeness · Chapter 6: Scheme · Chapter 7: Structure · Chapter 8: Abstraction · Chapter 9: Standards · Chapter 10: Readability · Chapter 11: Definitions · Chapter 12: Consistency · Chapter 13: Data In Section III, Validating Data Models, we will prepare for the model review (Chapter 14), cover tips to help during the model review (Chapter 15), and then review a data model based upon an actual project (Chapter 16).



A Handbook On Modern Databases


A Handbook On Modern Databases
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Author : Afifa Salsabil Fathima
language : en
Publisher: MileStone Research Publications
Release Date : 2025-02-03

A Handbook On Modern Databases written by Afifa Salsabil Fathima and has been published by MileStone Research Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-03 with Computers categories.


A comprehensive understanding of SQL is imperative for individuals involved in database-related tasks, be it application development, business intelligence, or data analysis. Proficiency in writing effective SQL queries not only enables users to extract meaningful insights from data but also ensures the efficient management of database resources. The knowledge gained from this chapter forms a solid foundation for adept database management, contributing to the overall success of data-driven applications and decision-making processes.



Nosql Data Modeling Using Mongodb As An Example And Recorded Live At Data Modeling Zone Us


Nosql Data Modeling Using Mongodb As An Example And Recorded Live At Data Modeling Zone Us
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Author : Austin Zellner
language : en
Publisher:
Release Date : 2020

Nosql Data Modeling Using Mongodb As An Example And Recorded Live At Data Modeling Zone Us written by Austin Zellner and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.


Recorded live at Data Modeling Zone! Follow along with MongoDB expert Austin Zellner and become competent in NoSQL data modeling in this sixth topic in the NoSQL Complete course. Know the difference between referencing data and embedding data. When in doubt, embed your data. Learn how to combine data and state in the same collection. Learn about modern use case patterns including microservices. Know how to model multi-document ACID transactions. Learn about master files and working files in MongoDB.



Graph Based Representation And Reasoning


Graph Based Representation And Reasoning
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Author : Dominik Endres
language : en
Publisher: Springer
Release Date : 2019-06-24

Graph Based Representation And Reasoning written by Dominik Endres and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-24 with Computers categories.


This book constitutes the proceedings of the 24th International Conference on Conceptual Structures, ICCS 2019, held in Marburg, Germany, in July 2019. The 14 full papers and 6 short papers presented were carefully reviewed and selected from 29 submissions. The proceedings also include one of the two invited talks. The papers focus on the representation of and reasoning with conceptual structures in a variety of contexts. ICCS 2019's theme was entitled "Graphs in Human and Machine Cognition."



Getting Mean With Mongo Express Angular And Node


Getting Mean With Mongo Express Angular And Node
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Author : Simon Holmes
language : en
Publisher: Simon and Schuster
Release Date : 2019-04-22

Getting Mean With Mongo Express Angular And Node written by Simon Holmes and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-22 with Computers categories.


Summary Getting MEAN, Second Edition teaches you how to develop full-stack web applications using the MEAN stack. This edition was completely revised and updated to cover MongoDB 4, Express 4, Angular 7, Node 11, and the latest mainstream release of JavaScript ES2015. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Juggling languages mid-application can radically slow down a full-stack web project. The MEAN stack—MongoDB, Express, Angular, and Node—uses JavaScript end to end, maximizing developer productivity and minimizing context switching. And you'll love the results! MEAN apps are fast, powerful, and beautiful. About the Book Getting MEAN, Second Edition teaches you how to develop full-stack web applications using the MEAN stack. Practical from the very beginning, the book helps you create a static site in Express and Node. Expanding on that solid foundation, you'll integrate a MongoDB database, build an API, and add an authentication system. Along the way, you'll get countless pro tips for building dynamic and responsive data-driven web applications! What's inside MongoDB 4, Express 4, Angular 7, and Node.js 11 MEAN stack architecture Mobile-ready web apps Best practices for efficiency and reusability About the Reader Readers should be comfortable with standard web application designs and ES2015-style JavaScript. About the Author Simon Holmes and Clive Harber are full-stack developers with decades of experience in JavaScript and other leading-edge web technologies. Table of Contents PART 1 - SETTING THE BASELINE Introducing full-stack development Designing a MEAN stack architecture PART 2 - BUILDING A NODE WEB APPLICATION Creating and setting up a MEAN project Building a static site with Node and Express Building a data model with MongoDB and Mongoose Writing a REST API: Exposing the MongoDB database to the application Consuming a REST API: Using an API from inside Express PART 3 - ADDING A DYNAMIC FRONT END WITH ANGULAR Creating an Angular application with TypeScript Building a single-page application with Angular: Foundations Building a single-page application with Angular: The next level PART 4 - MANAGING AUTHENTICATION AND USER SESSIONS Authenticating users, managing sessions, and securing APIs Using an authentication API in Angular applications