Nosql Data Modeling Essential Training
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Nosql Data Modeling Essential Training
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Author :
language : en
Publisher:
Release Date : 2018
Nosql Data Modeling Essential Training written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Get started with data modeling for NoSQL databases and learn how to work with common design patterns.
Nosql Data Modeling Essential Training
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Author : Robert Van Cleave
language : en
Publisher:
Release Date : 2018
Nosql Data Modeling Essential Training written by Robert Van Cleave and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Cassandra Data Modeling Essential Training
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Author : Dan Sullivan
language : en
Publisher:
Release Date : 2017
Cassandra Data Modeling Essential Training written by Dan Sullivan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Cassandra Data Modeling Essential Training
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Author :
language : en
Publisher:
Release Date : 2017
Cassandra Data Modeling Essential Training written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Learn about the architecture of Cassandra?a popular NoSQL database capable of handling large amounts of fast-changing data?and discover how to design Cassandra data models.
Data Modeling With Nosql Database
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Author : Sultan Ahmad
language : en
Publisher:
Release Date : 2021-03-30
Data Modeling With Nosql Database written by Sultan Ahmad and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-30 with categories.
● An important step in database implementation is the data modeling, because it facilitates the understanding of the project through key features that can prevent programming and operation errors. ● In database technologies, some of the new issues increasingly debated arenon-conventional applications, including NoSQL (Not only SQL) databases, whichwere initially created in response to the needs for better scalability, lowerlatency and higher flexibility in an era of bigdata and cloud computing. Thesenon-functional aspects are the main reason for using NoSQL database. ● Data modeling has an important role to play in NoSQL environments. The datamodeling process involves the creation of a diagram that represents the meaning of the data and the relationship between the data elements. Thus, understanding is a fundamental aspect of data modeling and a pattern for this kind of representation has few contributions for NoSQL databases. ● This book explains a NoSQL data modeling standard, introducing modeling techniques that can be used on document-oriented databases. We have considered Cassandra and Riak NoSQL databases because of the heterogeneous characteristics of each NoSQL database classification so that to fill the knowledge gap by studying the available non-relational databases in order to develop a systematic approach for solving problems of data persistence using these technologies. Ajit & Sultan.......
Data Modeling With Nosql Database
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Author : Ajit Singh
language : en
Publisher: Independently Published
Release Date : 2022-11-06
Data Modeling With Nosql Database written by Ajit Singh and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-06 with categories.
● An important step in database implementation is the data modeling, because it facilitates the understanding of the project through key features that can prevent programming and operation errors. ● In database technologies, some of the new issues increasingly debated are non-conventional applications, including NoSQL (Not only SQL) databases, which were initially created in response to the needs for better scalability, lower latency and higher flexibility in an era of bigdata and cloud computing. These non-functional aspects are the main reason for using NoSQL database. ● Data modeling has an important role to play in NoSQL environments. The data modeling process involves the creation of a diagram that represents the meaning of the data and the relationship between the data elements. Thus, understanding is a fundamental aspect of data modeling and a pattern for this kind of representation has few contributions for NoSQL databases. ● This edition (3rd) explains a NoSQL data modeling standard, introducing modeling techniques that can be used on document-oriented databases. We have considered Cassandra and Riak NoSQL databases because of the heterogeneous characteristics of each NoSQL database classification so that to fill the knowledge gap by studying the available non-relational databases in order to develop a systematic approach for solving problems of data persistence using these technologies. Ajit.............
Nosql For Mere Mortals
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Author : Dan Sullivan
language : en
Publisher: Addison-Wesley Professional
Release Date : 2015-04-06
Nosql For Mere Mortals written by Dan Sullivan and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-06 with Computers categories.
The Easy, Common-Sense Guide to Solving Real Problems with NoSQL The Mere Mortals® tutorials have earned worldwide praise as the clearest, simplest way to master essential database technologies. Now, there’s one for today’s exciting new NoSQL databases. NoSQL for Mere Mortals guides you through solving real problems with NoSQL and achieving unprecedented scalability, cost efficiency, flexibility, and availability. Drawing on 20+ years of cutting-edge database experience, Dan Sullivan explains the advantages, use cases, and terminology associated with all four main categories of NoSQL databases: key-value, document, column family, and graph databases. For each, he introduces pragmatic best practices for building high-value applications. Through step-by-step examples, you’ll discover how to choose the right database for each task, and use it the right way. Coverage includes --Getting started: What NoSQL databases are, how they differ from relational databases, when to use them, and when not to Data management principles and design criteria: Essential knowledge for creating any database solution, NoSQL or relational --Key-value databases: Gaining more utility from data structures --Document databases: Schemaless databases, normalization and denormalization, mutable documents, indexing, and design patterns --Column family databases: Google’s BigTable design, table design, indexing, partitioning, and Big Data Graph databases: Graph/network modeling, design tips, query methods, and traps to avoid Whether you’re a database developer, data modeler, database user, or student, learning NoSQL can open up immense new opportunities. As thousands of database professionals already know, For Mere Mortals is the fastest, easiest route to mastery.
Nosql Essential Training
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Author : Melanie McGee
language : en
Publisher:
Release Date : 2021
Nosql Essential Training written by Melanie McGee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
As the shiny new object in the data world, you might have heard a lot of people talk excitedly about NoSQL and all the things it can do. It's great in terms of flexibility, speed, and is easy to work with. It's super scalable, so it can accommodate increased numbers of users as websites and applications grow. But will it replace SQL? Will it make relational databases obsolete? In this course, Mel McGee explains just exactly what NoSQL is, the pros and cons, and tradeoffs you'll make when using NoSQL. Mel takes a high-level approach without delving into the details of any one NoSQL query language or solution, so if you're a developer looking for a bigger picture of NoSQL, or an entrepreneur wanting to explore options for your product, or just plain curious about non-relational databases, this course is for you.
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.
Data Modeling Master Class Training Manual
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Author : Steve Hoberman
language : en
Publisher:
Release Date : 2015-07
Data Modeling Master Class Training Manual written by Steve Hoberman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07 with categories.
This is the sixth edition of the training manual for the Data Modeling Master Class that Steve Hoberman teaches onsite and through public classes. This text can be purchased prior to attending the Master Class, the latest course schedule and detailed description can be found on Steve Hoberman's website, stevehoberman.com. The Master Class is a complete data modeling course, containing three days of practical techniques for producing conceptual, logical, and physical relational and dimensional and NoSQL data models. After learning the styles and steps in capturing and modeling requirements, you will apply a best practices approach to building and validating data models through the Data Model Scorecard. You will know not just how to build a data model, but how to build a data model well. Two case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects. Top 10 Objectives 1.Explain data modeling components and identify them on your projects by following a question-driven approach 2.Demonstrate reading a data model of any size and complexity with the same confidence as reading a book 3.Validate any data model with key "settings" (scope, abstraction, timeframe, function, and format) as well as through the Data Model Scorecard 4.Apply requirements elicitation techniques including interviewing, artifact analysis, prototyping, and job shadowing 5.Build relational and dimensional conceptual and logical data models, and know the tradeoffs on the physical side for both RDBMS and NoSQL solutions 6.Practice finding structural soundness issues and standards violations 7.Recognize when to use abstraction and where patterns and industry data models can give us a great head start 8.Use a series of templates for capturing and validating requirements, and for data profiling 9.Evaluate definitions for clarity, completeness, and correctness 10.Leverage the Data Vault and enterprise data model for a successful