#777 Год выпуска: 2014 Производитель: Infinite Skills Сайт производителя: infiniteskills.com Автор: Michael Blaha Продолжительность: 8:00 Тип раздаваемого материала: Видеоклипы Язык: Английский Описание: In this Learning Data Modeling training course, expert author Michael Blaha will teach you how to build data models, as well as prepare a data model for simple problems. This course is designed for users that have some programming experience, however, no data modeling experience is needed. You will start by learning about the data modeling development process, then jump into basic and advanced data modeling. From there, Michael will teach you how to create a UML data model, including finding classes, adding attributes, and simplifying the model. This video tutorial also covers how to translate a UML data model into an IE data model, model quality, the different kinds of data models, and database design. You will also learn how to create an SQL server database, an MS-Access database, and develop frameworks. Finally, Michael will teach you about data modeling patterns and database reverse engineering. Once you have completed this computer based training course, you will be fully capable of creating your own data models. Working files are included, allowing you to follow along with the author throughout the lessons.
Содержание
01. Getting Started 0101 About The Course 0102 About The Author 0103 What Is A Database? 0104 What Is A Data Model? 0105 How To Access Your Working Files
02. Data Model Development Process 0201 Data Model Inputs And Outputs 0202 Data Model Notations 0203 UML Versus IE - Conceptual, Logical And Physical
03. Basic Data Modeling 0301 Class And Attribute 0302 Operation 0303 Domain 0304 Association 0304 IE Entity Type And Relationship Type 0305 Association Name 0306 Association End 0307 Multiplicity - UML 0308 Multiplicity - IE 0309 Generalization - UML 0310 Generalization - IE 0311 Abstract Versus Concrete Superclass 0312 Practical Tips 0313 Self Assessment Test
04. Advanced Data Modeling 0401 Identity 0402 Derived Data 0403 Current Versus Historical Data 0404 Association Class 0405 Ordered Association 0406 Qualified Association - UML 0407 Qualified Association - IE 0408 Large Taxonomies 0409 Package 0410 Abridged UML Metamodel 0411 Abridged IE Metamodel 0412 Modeling Pitfalls 0413 Practical Tips 0414 Self Assessment Test
05. Create A UML Data Model 0501 Problem Statement 0502 Finding Classes 0503 Finding Associations - Part 1 0504 Finding Associations - Part 2 0505 Finding Generalizations 0506 Iterating And Refining The Model - Part 1 0507 Iterating And Refining The Model - Part 2 0508 Adding Attributes 0509 Cleaning Up Layout 0510 Simplifying The Model 0511 Evolving A Model - Part 1 0512 Evolving A Model - Part 2 0513 Enterprise Architect Techniques - Part 1 0514 Enterprise Architect Techniques - Part 2 0515 Enterprise Architect Techniques - Part 3
06. Translate A UML Data Model Into An IE Data Model 0601 Creating Subject Areas 0602 Creating Entity Types 0603 Creating Domains 0604 Adding Attributes - Part 1 0605 Adding Attributes - Part 2 0606 Creating Relationship Types - Part 1 0607 Creating Relationship Types - Part 2 0608 Creating Relationship Types - Part 3 0609 Subtyping 0610 Adding Alternate Keys 0611 Cleaning Up The Layout 0612 ERwin Techniques - Part 1 0613 ERwin Techniques - Part 2
07. Model Quality 0701 Model Quality 0702 Normal Forms 0703 Constraints 0704 Hillard Graph Complexity 0705 Hoberman Data Model Scorecard
08. Kinds Of Data Models 0801 Operational Data Models 0802 Enterprise Data Models 0803 Data Warehouses - Part 1 0804 Data Warehouses - Part 2 0805 Data Warehouses - Part 3 0806 Master Data Models
09. Database Design 0901 Schema Adjustments 0902 Attribute Details - Part 1 0903 Attribute Details - Part 2 0904 Attribute Details - Part 3 0905 Primary And Alternate Keys 0906 Indexes 0907 Referential Integrity - Part 1 0908 Referential Integrity - Part 2 0909 Check Constraints - Part 1 0910 Check Constraints - Part 2 0911 Views 0912 Other Aspects Of Design 0913 Self Assessment Test
10. Create A SQL Server Database 1001 Creating A New Database 1002 Executing Schema 1003 Inspecting Metadata 1004 Loading Sample Data 1005 Querying Sample Data
11. Create An MS-Access Database 1101 Generating An ERwin Schema 1102 Creating Tables 1103 Creating Indexes 1104 Creating Constraints And Default Values 1105 Defining Foreign Keys 1106 Creating Views 1107 Loading Sample Data 1108 Querying Sample Data
12. Software Engineering 1201 Development Frameworks 1202 Agile Data Modelling 1203 Documenting A Model - Part 1 1204 Documenting A Model - Part 2 1205 Presenting A Model
13. Data Modeling Patterns 1301 Overview 1302 Tree - Hardcoded 1303 Tree - Simple 1304 Tree - Structured 1305 Tree - Overlapping 1306 Tree - Changing Over Time 1307 Tree - Degenerate Node and Edge
14. Database Reverse Engineering 1401 Motives 1402 Comparison With Forward Engineering 1403 Outputs 1404 Inputs 1405 Process 1406 Principles 1407 Example - Part 1 1408 Example - Part 2
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