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Data Modeling Master Class Training Manual 5th Edition
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Book Synopsis Data Modeling Master Class Training Manual 5th Edition by : Steve Hoberman
Download or read book Data Modeling Master Class Training Manual 5th Edition written by Steve Hoberman and published by Technics Publications, LLC. This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Modeling Master Class Training Manual by : Steve Hoberman
Download or read book Data Modeling Master Class Training Manual written by Steve Hoberman and published by . This book was released on 2015-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Data Modeling Master Class Training Manual 9th Edition by : Steve Hoberman
Download or read book Data Modeling Master Class Training Manual 9th Edition written by Steve Hoberman and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Modeling Master Class Training Manual by : Steve Hoberman
Download or read book Data Modeling Master Class Training Manual written by Steve Hoberman and published by Technics Publications, LLC. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Modeling Master Class Training Manual 7th Edition by : Steve Hoberman
Download or read book Data Modeling Master Class Training Manual 7th Edition written by Steve Hoberman and published by . This book was released on 2017-06 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Modeling Master Class Training Manual by : Steve Hoberman
Download or read book Data Modeling Master Class Training Manual written by Steve Hoberman and published by . This book was released on 2019-05-14 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Modeling Master Class Training Manual 2nd Edition by : Steve Hoberman
Download or read book Data Modeling Master Class Training Manual 2nd Edition written by Steve Hoberman and published by Technics Publications LLC. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Modeling Fundamentals by : Steve Hoberman
Download or read book Data Modeling Fundamentals written by Steve Hoberman and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.
Book Synopsis Physical Data Modeling by : Steve Hoberman
Download or read book Physical Data Modeling written by Steve Hoberman and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.
Book Synopsis The Data Modeling Handbook by : Michael C. Reingruber
Download or read book The Data Modeling Handbook written by Michael C. Reingruber and published by John Wiley & Sons. This book was released on 1994-12-17 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical, field-tested reference doesn't just explain the characteristics of finished, high-quality data models--it shows readers exactly how to build one. It presents rules and best practices in several notations, including IDEFIX, Martin, Chen, and Finkelstein. The book offers dozens of real-world examples and go beyond basic theory to provide users with practical guidance.
Book Synopsis Data Modeling Made Simple by : Steve Hoberman
Download or read book Data Modeling Made Simple written by Steve Hoberman and published by Technics Publications, LLC. This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ever have a bad data day? If you are a business user, architect, analyst, designer or developer, then you have probably had some bad data days. It comes with the territory. Overcoming these problems is much easier if you have an in-depth understanding of the actual data. That's where a data model comes in handy. It's a diagram that uses text and symbols to represent groupings of data, giving you a clear picture of your business and application environment. The book provides the tools you need to read, create and validate models of your business and applications. Contains everything about modelling you need to know but were too afraid to ask, such as: What are the traditional and non-traditional uses of a data model? How do subject area, logical, and physical data models differ? When do I build a BSAM, ASAM, or CSAM? What is the easiest way to apply normalisation? Where can I best leverage abstraction? How do I decide whether to use denormalisation or dimensionality? What are primary, foreign, alternate, virtual, and surrogate keys? What is the best approach to building the models? How can I use the Scorecard system to validate a data model? Includes over 30 exercises to reinforce concepts and sharpen your skills!
Book Synopsis Data Modeling Made Simple with Erwin DM by : Harris Jeff
Download or read book Data Modeling Made Simple with Erwin DM written by Harris Jeff and published by . This book was released on 2020-06 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Conceptual Data Modeling by : Steve Hoberman
Download or read book Conceptual Data Modeling written by Steve Hoberman and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "A data model represents a precise information landscape, and there are different levels of modeling depending on the audience and the model's purpose. A conceptual data model (CDM) is the highest-level of modeling and is designed to capture business needs and help both business and IT professionals agree on a common set of terms and definitions. It is an extremely powerful data model and this video will not only explain the CDM, but also work with you on a hands-on exercise covering the five steps for creating a CDM. Learn why the CDM is so important and see several actual CDMs and learn how each was built. This video was recorded live during Steve Hoberman's Data Modeling Master Class."--Resource description page.
Book Synopsis Data Modeling Essentials by : Graeme Simsion
Download or read book Data Modeling Essentials written by Graeme Simsion and published by Elsevier. This book was released on 2004-12-03 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Modeling Essentials, Third Edition, covers the basics of data modeling while focusing on developing a facility in techniques, rather than a simple familiarization with "the rules". In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice. This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises. This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective. Thorough coverage of the fundamentals and relevant theory Recognition and support for the creative side of the process Expanded coverage of applied data modeling includes new chapters on logical and physical database design New material describing a powerful technique for model verification Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict
Book Synopsis Data Modeling Essentials by : Graeme C. Simsion
Download or read book Data Modeling Essentials written by Graeme C. Simsion and published by Van Nostrand Reinhold Company. This book was released on 1994 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: An innovative "how-to" guide and design aid to data modeling. This book discusses the theory and practice of data modeling as a design activity, and shows the reader how to increase quality and stimulate creativity with new modeling approaches. The book is useful as both a basic learning tool, and a thought provoking guide to higher achievement in designing and executing data models.
Book Synopsis Data Modeling Made Simple with CA ERwin Data Modeler R8 by : Donna Burbank
Download or read book Data Modeling Made Simple with CA ERwin Data Modeler R8 written by Donna Burbank and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Modeling Made Simple with CA ERwin Data Modeler r8 will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices, and how to apply these principles with CA ERwin Data Modeler r8. You'll build many CA ERwin data models along the way, mastering first the fundamentals and later in the book the more advanced features of CA ERwin Data Modeler. This book combines real-world experience and best practices with down to earth advice, humor, and even cartoons to help you master the following ten objectives: Understand the basics of data modeling and relational theory, and how to apply these skills using CA ERwin Data Modeler Read a data model of any size and complexity with the same confidence as reading a book Understand the difference between conceptual, logical, and physical models, and how to effectively build these models using CA ERwin's Data Modelers Design Layer Architecture Apply techniques to turn a logical data model into an efficient physical design and vice-versa through forward and reverse engineering, for both 'top down' and bottom-up design Learn how to create reusable domains, naming standards, UDPs, and model templates in CA ERwin Data Modeler to reduce modeling time, improve data quality, and increase enterprise consistency Share data model information with various audiences using model formatting and layout techniques, reporting, and metadata exchange Use the new workspace customization features in CA ERwin Data Modeler r8 to create a workflow suited to your own individual needs Leverage the new Bulk Editing features in CA ERwin Data Modeler r8 for mass metadata updates, as well as import/export with Microsoft Excel Compare and merge model changes using CA ERwin Data Modelers Complete Compare features Optimize the organization and layout of your data models through the use of Subject Areas, Diagrams, Display Themes, and more Section I provides an overview of data modeling: what it is, and why it is needed. The basic features of CA ERwin Data Modeler are introduced with a simple, easy-to-follow example. Section II introduces the basic building blocks of a data model, including entities, relationships, keys, and more. How-to examples using CA ERwin Data Modeler are provided for each of these building blocks, as well as 'real world' scenarios for context. Section III covers the creation of reusable standards, and their importance in the organization. From standard data modeling constructs such as domains to CA ERwin-specific features such as UDPs, this section covers step-by-step examples of how to create these standards in CA ERwin Data Modeling, from creation, to template building, to sharing standards with end users through reporting and queries. Section IV discusses conceptual, logical, and physical data models, and provides a comprehensive case study using CA ERwin Data Modeler to show the interrelationships between these models using CA ERwin's Design Layer Architecture. Real world examples are provided from requirements gathering, to working with business sponsors, to the hands-on nitty-gritty details of building conceptual, logical, and physical data models with CA ERwin Data Modeler r8.
Book Synopsis Data Modeling for Information Professionals by : Bob Schmidt
Download or read book Data Modeling for Information Professionals written by Bob Schmidt and published by Prentice Hall. This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: PLEASE PROVIDE ?
