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Data Modeling Made Simple With Er Studio Data Architect

Author: Steve Hoberman
Publisher: Technics Publications
ISBN: 1634620941
Size: 73.74 MB
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Build a working knowledge of data modeling concepts and best practices, along with how to apply these principles with ER/Studio. This second edition includes numerous updates and new sections including an overview of ER/Studio’s support for agile development, as well as a description of some of ER/Studio’s newer features for NoSQL, such as MongoDB’s containment structure.

Data Modeling Made Simple

Author: Steve Hoberman
Publisher: Technics Publications
ISBN: 163462016X
Size: 56.77 MB
Format: PDF, ePub, Docs
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Data Modeling Made Simple will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives: Know when a data model is needed and which type of data model is most effective for each situation Read a data model of any size and complexity with the same confidence as reading a book Build a fully normalized relational data model, as well as an easily navigatable dimensional model Apply techniques to turn a logical data model into an efficient physical design Leverage several templates to make requirements gathering more efficient and accurate Explain all ten categories of the Data Model Scorecard Learn strategies to improve your working relationships with others Appreciate the impact unstructured data has, and will have, on our data modeling deliverables Learn basic UML concepts Put data modeling in context with XML, metadata, and agile development Book Review by Johnny Gay In this book review, I address each section in the book and provide what I found most valuable as a data modeler. I compare, as I go, how the book's structure eases the new data modeler into the subject much like an instructor might ease a beginning swimmer into the pool. This book begins like a Dan Brown novel. It even starts out with the protagonist, our favorite data modeler, lost on a dark road somewhere in France. In this case, what saves him isn't a cipher, but of all things, something that's very much like a data model in the form of a map! The author deems they are both way-finding tools. The chapters in the book are divided into 5 sections. The chapters in each section end with an exercise and a list of the key points covered to reinforce what you've learned. I find myself comparing the teaching structure of the book to the way most of us learn to swim.

Conceptual Data Modeling And Database Design A Fully Algorithmic Approach Volume 1

Author: Christian Mancas
Publisher: CRC Press
ISBN: 1498728448
Size: 53.89 MB
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This new book aims to provide both beginners and experts with a completely algorithmic approach to data analysis and conceptual modeling, database design, implementation, and tuning, starting from vague and incomplete customer requests and ending with IBM DB/2, Oracle, MySQL, MS SQL Server, or Access based software applications. A rich panoply of solutions to actual useful data sub-universes (e.g. business, university, public and home library, geography, history, etc.) is provided, constituting a powerful library of examples. Four data models are presented and used: the graphical Entity-Relationship, the mathematical EMDM, the physical Relational, and the logical deterministic deductive Datalog ones. For each one of them, best practice rules, algorithms, and the theory beneath are clearly separated. Four case studies, from a simple public library example, to a complex geographical study are fully presented, on all needed levels. Several dozens of real-life exercises are proposed, out of which at least one per chapter is completely solved. Both major historical and up-to-date references are provided for each of the four data models considered. The book provides a library of useful solutions to real-life problems and provides valuable knowledge on data analysis and modeling, database design, implementation, and fine tuning.

Modeling Business Processes

Author: Wil van der Aalst
Publisher: MIT Press
ISBN: 0262015382
Size: 56.97 MB
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An introduction to the modeling of business information systems, with processes formally modeled using Petri nets. This comprehensive introduction to modeling business-information systems focuses on business processes. It describes and demonstrates the formal modeling of processes in terms of Petri nets, using a well-established theory for capturing and analyzing models with concurrency. The precise semantics of this formal method offers a distinct advantage for modeling processes over the industrial modeling languages found in other books on the subject. Moreover, the simplicity and expressiveness of the Petri nets concept make it an ideal language for explaining foundational concepts and constructing exercises. After an overview of business information systems, the book introduces the modeling of processes in terms of classical Petri nets. This is then extended with data, time, and hierarchy to model all aspects of a process. Finally, the book explores analysis of Petri net models to detect design flaws and errors in the design process. The text, accessible to a broad audience of professionals and students, keeps technicalities to a minimum and offers numerous examples to illustrate the concepts covered. Exercises at different levels of difficulty make the book ideal for independent study or classroom use.

Data Modeling For Mongodb

Author: Steve Hoberman
Publisher: Technics Publications
ISBN: 1634620410
Size: 63.58 MB
Format: PDF
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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.

Uml Requirements Modeling For Business Analysts

Author: Norman Daoust
Publisher: Technics Publications
ISBN: 1634620429
Size: 34.21 MB
Format: PDF, ePub, Docs
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This book provides you with a collection of best practices, guidelines, and tips for using the Unified Modeling Language (UML) for business analysis. The contents have been assembled over the years based on experience and documented best practices. Over sixty easy to understand UML diagram examples will help you to apply these ideas immediately. If you use, expect to use, or think you should use the Unified Modeling Language (UML) or use cases in your business analysis activities, this book will help you: • communicate more succinctly and effectively with your stakeholders including your software development team, • increase the likelihood that your requirements will be reviewed and understood, • reduce requirements analysis, documentation, and review time. The first three chapters explain the reasons for utilizing the UML for business analysis, present a brief history of the UML and its diagram categories, and describe a set of general modeling guidelines and tips applicable to all of the UML diagram types. Each of the next thirteen chapters is dedicated to a different UML diagram type: 1. Use Case Diagrams 2. Activity Diagrams 3. Interaction Overview Diagrams 4. Class Diagrams 5. Object Diagrams 6. State Machine Diagrams 7. Timing Diagrams 8. Sequence Diagrams 9. Communication Diagrams 10. Composite Structure Diagrams 11. Component Diagrams 12. Deployment Diagrams 13. Package Diagrams The next two chapters explain additional diagram types that are important for business analysts and that can be created using UML notation: • Context Diagrams using Communication diagram notation • Data Models using Class diagram notation These chapters are followed by a chapter that describes criteria for selecting the various diagram types. The final chapter presents a case study.