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Data Modeling Made Simple with ER/Studio Data Architect: Adapting to Agile Data Modeling in a Big Data World

Book Description

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. You will build many ER/Studio data models along the way, applying best practices to master these ten objectives:
  1. Know why a data model is needed and which ER/Studio models are the most appropriate for each situation
  2. Understand each component on the data model and how to represent and create them in ER/Studio
  3. Know how to leverage ER/Studio's latest features including those assisting agile teams and forward and reverse engineering of NoSQL databases
  4. Know how to apply all the foundational features of ER/Studio
  5. Be able to build relational and dimensional conceptual, logical, and physical data models in ER/Studio
  6. Be able to apply techniques such as indexing, transforms, and forward engineering to turn a logical data model into an efficient physical design
  7. Improve data model quality and impact analysis results by leveraging ER/Studio's lineage functionality and compare/merge utility
  8. Be able to apply ER/Studio's data dictionary features
  9. Learn ways of sharing the data model through reporting and through exporting the model in a variety of formats
  10. Leverage ER/Studio's naming functionality to improve naming consistency, including the new Automatic Naming Translation feature.
This book contains four sections:

Section I introduces data modeling and the ER/Studio landscape. Learn why data modeling is so critical to software development and even more importantly, why data modeling is so critical to understanding the business. You will learn about the newest features in ER/Studio (including features on big data and agile), and the ER/Studio environment. By the end of this section, you will have created and saved your first data model in ER/Studio and be ready to start modeling in Section II!

Section II explains all of the symbols and text on a data model, including entities, attributes, relationships, domains, and keys. By the time you finish this section, you will be able to 'read' a data model of any size or complexity, and create a complete data model in ER/Studio.

Section III explores the three different levels of models: conceptual, logical, and physical. A conceptual data model (CDM) represents a business need within a defined scope. The logical data model (LDM) represents a detailed business solution, capturing the business requirements without complicating the model with implementation concerns such as software and hardware. The physical data model (PDM) represents a detailed technical solution. The PDM is the logical data model compromised often to improve performance or usability. The PDM makes up for deficiencies in our technology. By the end of this section you will be able to create conceptual, logical, and physical data models in ER/Studio.

Section IV discusses additional features of ER/Studio. These features include data dictionary, data lineage, automating tasks, repository and portal, exporting and reporting, naming standards, and compare and merge functionality.

Table of Contents

  1. Read me first!
    1. Conventions Used in This Book
    2. What’s Different in the 2nd Edition?
    3. How to Get the Most out of This Book
  2. SECTION I Foundation
  3. CHAPTER 1 Data Model Overview
    1. Finding Your Way
    2. Representing an Information Landscape
    3. Leveraging the Data Model
    4. Embarking on Our Publishing Adventure
    5. EXERCISE 1.1: Educating Your Neighbor
  4. CHAPTER 2 ER/Studio Functionality
    1. EXERCISE 2.1: Learning More About the ER/Studio Family
    2. New Features in ER/Studio
    3. My “Top 10” Favorite Features of ER/Studio
    4. EXERCISE 2.2: Installing and Starting ER/Studio
  5. CHAPTER 3 ER/Studio Landscape
    1. Using the Windows
    2. Using the Menus
    3. Using the Toolbars
    4. Using Keyboard Commands
    5. Using the Status Bar
    6. EXERCISE 3.1: Creating a New Data Model
    7. EXERCISE 3.2: Saving Your Data Model
    8. EXERCISE 3.3: Closing and Opening Existing Data Models
    9. EXERCISE 3.4: Getting Comfortable with ER/Studio
  6. SECTION II Data Model Objects
  7. CHAPTER 4 Entities
    1. Entity Explanation
    2. Entity Types
    3. Entities in ER/Studio
    4. EXERCISE 4.1: Creating Entities
  8. CHAPTER 5 Submodels
    1. Submodel Explanation
    2. Submodels in ER/Studio
    3. EXERCISE 5.1: Changing Settings in Submodels
    4. EXERCISE 5.2: Creating Three More Submodels
    5. EXERCISE 5.3: Creating Title Blocks for Each Submodel
  9. CHAPTER 6 Attributes and Domains
    1. Attribute Explanation
    2. Attribute Types
    3. Attributes in ER/Studio
    4. EXERCISE 6.1: Creating Attributes
    5. Key Explanation
    6. EXERCISE 6.2: Clarifying Customer ID
    7. Keys in ER/Studio
    8. EXERCISE 6.3: Creating Keys
    9. Domain Explanation
  10. CHAPTER 7 Relationships
    1. Relationship Explanation
    2. Relationship Types
    3. Cardinality
    4. Independent vs. Dependent Entities
    5. Recursion
    6. Containment
    7. Subtyping
    8. EXERCISE 7.1: Reading a Model
    9. Data Modeling Notations
    10. Relationships in ER/Studio
    11. EXERCISE 7.2: Creating Relationships
  11. SECTION III Conceptual, Logical, and Physical Data Models
  12. CHAPTER 8 Conceptual Data Models
    1. Conceptual Data Model Explanation
    2. Relational and Dimensional Conceptual Data Models
    3. Creating a Conceptual Data Model
    4. EXERCISE 8.1: Creating a Conceptual Data Model
    5. EXERCISE 8.3: Segmenting the Publisher CDM into Submodels
    6. EXERCISE 8.4: Creating a Conceptual Data Model for Your Organization
  13. CHAPTER 9 Logical Data Models
    1. Logical Data Model Explanation
    2. Relational and Dimensional Logical Data Models
    3. Creating a Relational Logical Data Model
    4. Creating a Dimensional Logical Data Model
    5. EXERCISE 9.1: Creating a Dimensional Logical Data Model
  14. CHAPTER 10 Physical Data Models
    1. Physical Data Model Explanation
    2. Relational and Dimensional Physical Data Models
    3. Creating a Physical Data Model in ER/Studio
    4. Generating a Database Using ER/Studio
    5. Editing Tables
    6. Customizing Datatype Mapping
    7. Denormalization
    8. Denormalizing in ER/Studio
    9. EXERCISE 10.1: Denormalizing
    11. Views in ER/Studio
    12. EXERCISE 10.2: Creating Views
    13. Indexing
    14. Indexing in ER/Studio
    15. EXERCISE 10.3: Indexing
    16. Partitioning
    17. Partitioning in ER/Studio
    18. EXERCISE 10.4: Partitioning
    19. EXERCISE 10.5: Tracing from Physical Back to Logical
  15. SECTION IV Additional ER/Studio Features
  16. CHAPTER 11 Data Dictionary
    1. Importing a Data Dictionary
    2. Types of Objects Imported from a Data Dictionary
  17. CHAPTER 12 Data Lineage
    1. Using the Data Lineage Tab
    2. Defining Source Systems in ER/Studio
    3. Creating Data Movement Rules in ER/Studio
    4. Creating a Data Flow in ER/Studio
    5. Using the Table Editor to Further Document Lineage
    6. Using the Column Editor to Further Document Lineage
    7. Exercise 12.1: Creating a Data Lineage
    8. A Less Formal Way to Connect Things: User-Defined Mappings
  18. CHAPTER 13 Importing, Exporting, Printing, and Reporting
    1. Importing into ER/Studio
    2. Exporting out of ER/Studio
    3. Printing in ER/Studio
    4. Reporting in ER/Studio
    5. Exercise 13.1: Importing, Exporting, Printing, and Reporting
  19. CHAPTER 14 Naming Standards
    1. Creating a Naming Standards Template
    2. Applying the Naming Standards Utility
    3. Assigning Naming Standards to Objects
    4. Automatic Naming Translation
    5. Exercise 14.1: Creating a Naming Standard Template
  20. CHAPTER 15 Compare/Merge Utility
    1. Comparing Models and Submodels in ER/Studio
    2. Exercise 15.1: Running the Compare and Merge Utility
  21. CHAPTER 16 Features for Agile Teams and Continuous Improvement
    1. Macros
    2. Reusable Procedure Logic
    3. Change Management
    4. Named Releases
    5. Model Validation
  22. APPENDIX A References
  23. APPENDIX B Answers to Exercises
    1. EXERCISE 1.1: Educating Your Neighbor
    2. EXERCISE 5.1: Changing Settings in Submodels
    3. EXERCISE 6.2: Clarifying Customer ID
    4. EXERCISE 7.1: Reading a Model
    5. EXERCISE 8.1: Creating a Conceptual Data Model
  24. APPENDIX C Glossary
  25. APPENDIX D ER/Studio Commands Quick Reference
    1. Most Frequently Used Commands
    2. Model Level Commands
    3. Entity and Table Level Commands
    4. Sublevel Commands
    5. Attribute and Key Commands
    6. Relationship Commands
    7. Macro Commands
  26. Index