Data Modeling Master Class Training Manual

Author: Steve Hoberman
Publisher:
ISBN: 9781634620901
Category :
Languages : en
Pages : 0

Book Description
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

Data Modeling Master Class Training Manual 9th Edition

Author: Steve Hoberman
Publisher:
ISBN: 9781634629072
Category :
Languages : en
Pages :

Book Description
This is the ninth 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.

Data Modeling Master Class Training Manual 7th Edition

Author: Steve Hoberman
Publisher:
ISBN: 9781634621946
Category : Computers
Languages : en
Pages : 346

Book Description
This is the seventh 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(R). 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(R) 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 enterprise architecture.

Data Modeling Master Class Training Manual

Author: Steve Hoberman
Publisher:
ISBN: 9781634622110
Category :
Languages : en
Pages : 332

Book Description
This is the eighth 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(R). You will know not just how to build a data model, but how to build a data model well. Three case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects. Top 5 Objectives Determine how and when to use each data modeling component Apply techniques to elicit data requirements as a prerequisite to building a data model Build relational and dimensional conceptual, logical, and physical data models Incorporate supportability and extensibility features into the data model Assess the quality of a data model.

Data Modeling Master Class Training Manual 5th Edition

Author: Steve Hoberman
Publisher: Technics Publications, LLC
ISBN: 9781935504887
Category : Data structures (Computer science)
Languages : en
Pages : 0

Book Description
This is the fifth 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.

Data Modeling Master Class Training Manual

Author: Steve Hoberman
Publisher: Technics Publications, LLC
ISBN: 9781935504160
Category : Data structures (Computer science)
Languages : en
Pages : 0

Book Description
This is the third 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.

Data Modeling Master Class Training Manual 2nd Edition

Author: Steve Hoberman
Publisher: Technics Publications LLC
ISBN: 9781935504061
Category : Data structures (Computer science)
Languages : en
Pages : 0

Book Description
A training manual for the Data Modelling Master Class. It includes a course on requirements gathering and data modelling, containing four days of practical techniques for producing solid relational and dimensional data models.

Data Modeling Fundamentals

Author: Steve Hoberman
Publisher:
ISBN: 9781634623209
Category :
Languages : en
Pages :

Book Description
"The Data Modeling 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. This video contains a majority of the content from the first module in this course. For more on the Data Modeling Master Class, please visit SteveHoberman.com. This video provides an introduction into the field of data modeling by defining data model concepts and terms, along with why the data modeling process is so important and warnings of pitfalls to avoid. Shortly after the video starts, you will complete a very important exercise illustrating the four important gaps filled by data models. Next, we will explain data modeling concepts and terminology including entities, attributes, relationships, candidate keys, and subtypes, and provide you with a set of questions you can ask to quickly and precisely build a data model. Demonstrate reading a data model of any size and complexity with the same confidence as reading a book. We will complete several exercises, including one on creating a data model based upon an existing set of data."--Resource description page.

Mastering Data Modeling

Author: John Carlis
Publisher: Addison-Wesley Professional
ISBN: 0134176537
Category : Computers
Languages : en
Pages : 629

Book Description
Data modeling is one of the most critical phases in the database application development process, but also the phase most likely to fail. A master data modeler must come into any organization, understand its data requirements, and skillfully model the data for applications that most effectively serve organizational needs. Mastering Data Modeling is a complete guide to becoming a successful data modeler. Featuring a requirements-driven approach, this book clearly explains fundamental concepts, introduces a user-oriented data modeling notation, and describes a rigorous, step-by-step process for collecting, modeling, and documenting the kinds of data that users need. Assuming no prior knowledge, Mastering Data Modeling sets forth several fundamental problems of data modeling, such as reconciling the software developer's demand for rigor with the users' equally valid need to speak their own (sometimes vague) natural language. In addition, it describes the good habits that help you respond to these fundamental problems. With these good habits in mind, the book describes the Logical Data Structure (LDS) notation and the process of controlled evolution by which you can create low-cost, user-approved data models that resist premature obsolescence. Also included is an encyclopedic analysis of all data shapes that you will encounter. Most notably, the book describes The Flow, a loosely scripted process by which you and the users gradually but continuously improve an LDS until it faithfully represents the information needs. Essential implementation and technology issues are also covered. You will learn about such vital topics as: The fundamental problems of data modeling The good habits that help a data modeler be effective and economical LDS notation, which encourages these good habits How to read an LDS aloud--in declarative English sentences How to write a well-formed (syntactically correct) LDS How to get users to name the parts of an LDS with words from their own business vocabulary How to visualize data for an LDS A catalog of LDS shapes that recur throughout all data models The Flow--the template for your conversations with users How to document an LDS for users, data modelers, and technologists How to map an LDS to a relational schema How LDS differs from other notations and why "Story interludes" appear throughout the book, illustrating real-world successes of the LDS notation and controlled evolution process. Numerous exercises help you master critical skills. In addition, two detailed, annotated sample conversations with users show you the process of controlled evolution in action.

Physical Data Modeling

Author: Steve Hoberman
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
"The Data Modeling 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. This video contains the physical data modeling module. For more on the Data Modeling Master Class, please visit SteveHoberman.com. Learn all about physical data modeling. The techniques of denormalizing, indexing, building views, and creating partitions are covered. Learn about the five different types of denormalization: standard, FUBES, repeating attributes, aggregation, and summarization. Understand both horizontal and vertical partitioning. Master several dimensional modeling concepts including star schemas, snowflakes, degenerate dimensions, junk dimensions, and slowly changing dimensions."--Resource description page.