Автор: Hoberman, Mary Ann Emberley, Michael Название: You read to me, i`ll read to you 2 ISBN: 0316043516 ISBN-13(EAN): 9780316043519 Издательство: Little Brown Рейтинг: Цена: 1240.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A unique collection of stories in verse that help children learn to read
Описание: From New York Times best-selling author and Children's Poet Laureate Mary Ann Hoberman comes a new collection of fresh read-aloud takes on eight favorite fairy tales, including "The Three Bears," "Cinderella," and "Little Red Riding Hood." Designed with emerging readers in mind, each of the tales is told in short rhyming dialogues--with each character's lines indicated by a different color-to be used as a script for two voices to read separately and together. Using traditional reading teaching techniques like alliteration, rhyme, repetition, and short sentences), the text invites young children to read along, while Michael Emberley's lively illustrations enhance the stories' humor and high spirits. Goldilocks, the Little Red Hen, the Three Little Pigs, and many more beloved characters star in these tales-with-a-twist that are perfect for early and reluctant readers, readers' theater, and bedtime fun. A 2005 Notable Children's Book in the Language Arts by the Children's Literature Assembly of the National Council of Teacher of English. Also chosen as a 2004 Gryphon Award Honor Book by the Center for Children's Books.
Автор: Hoberman Mary Ann Название: The Llama Who Had No Pajama: 100 Favorite Poems ISBN: 0152055711 ISBN-13(EAN): 9780152055714 Издательство: Hachette Book Group Цена: 939.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Mary Ann Hoberman and Michael Emberley have added Aesop's fables to their bestselling and award-winning series Rediscover familiar tales and find new favorites in this irresistible fifth YOU READ TO ME collaboration. These stories of classic characters-from wise ants and kind mice to sly foxes and hungry wolves-are fables as you've never seen them before With clear, color-coded typography and clever illustrations, this book "in two voices" uses traditional reading teaching techniques-alliteration, rhyme, and repetition-to invite young children to read along with peers or with an adult.
Автор: Hoberman J Название: Film After Film ISBN: 1781681430 ISBN-13(EAN): 9781781681435 Издательство: Неизвестно Рейтинг: Цена: 3965.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: How the digital turn and 9/11 have changed motion picture history.
Автор: Hoberman, Mary Ann Название: House Is a House for Me, A ISBN: 0142407739 ISBN-13(EAN): 9780142407738 Издательство: Random House (USA) Рейтинг: Цена: 827.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Where does everyone?and everything?live? A House Is a House for Me is a rollicking rhyme about houses. Some of the houses are familiar, such as an anthill and a dog kennel, while others are surprising, such as a corn husk and a pea pod. This longtime favorite is filled with pictures that parents and children will want to look at again and again in a beautifully produced, deluxe fullsized edition.
Автор: Hoberman Mary Ann Название: Miss Mary Mack ISBN: 0316537349 ISBN-13(EAN): 9780316537346 Издательство: Little Brown Рейтинг: Цена: 1061.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A lively picture book adaptation of the well-known children`s hand-clapping rhyme, perfect for the whole family.
Автор: Hoberman, Steve Название: Data model scorecard ISBN: 1634620828 ISBN-13(EAN): 9781634620826 Издательство: Gazelle Book Services Рейтинг: Цена: 10937.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Data models are the main medium used to communicate data requirements from business to IT, and within IT from analysts, modelers, and architects, to database designers and developers. Therefore it's essential to get the data model right. But how do you determine right? That's where the Data Model Scorecard(R) comes in.
The Data Model Scorecard is a data model quality scoring tool containing ten categories aimed at improving the quality of your organization's data models. Many of my consulting assignments are dedicated to applying the Data Model Scorecard to my client's data models - I will show you how to apply the Scorecard in this book.
This book, written for people who build, use, or review data models, contains the Data Model Scorecard template and an explanation along with many examples of each of the ten Scorecard categories. There are three sections:
In Section I, Data Modeling and the Need for Validation, receive a short data modeling primer in Chapter 1, understand why it is important to get the data model right in Chapter 2, and learn about the Data Model Scorecard in Chapter 3.
In Section II, Data Model Scorecard Categories, we will explain each of the ten categories of the Data Model Scorecard. There are ten chapters in this section, each chapter dedicated to a specific Scorecard category:
Chapter 4: Correctness
Chapter 5: Completeness
Chapter 6: Scheme
Chapter 7: Structure
Chapter 8: Abstraction
Chapter 9: Standards
Chapter 10: Readability
Chapter 11: Definitions
Chapter 12: Consistency
Chapter 13: Data
In Section III, Validating Data Models, we will prepare for the model review (Chapter 14), cover tips to help during the model review (Chapter 15), and then review a data model based upon an actual project (Chapter 16).
Описание: 2019 Choice Outstanding Academic Title Jewish writers have long had a sense of place in the United States, and interpretations of American geography have appeared in Jewish American literature from the colonial era forward. But troublingly, scholarship on Jewish American literary history often limits itself to an immigrant model, situating the Jewish American literary canon firmly and inescapably among the immigrant authors and early environments of the early twentieth century. In A Hundred Acres of America, Michael Hoberman combines literary history and geography to restore Jewish American writers to their roles as critical members of the American literary landscape from the 1850s to the present, and to argue that Jewish history, American literary history, and the inhabitation of American geography are, and always have been, contiguous entities.
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.
Автор: Hoberman, Steve Название: Data modeling master class training manual ISBN: 1634621948 ISBN-13(EAN): 9781634621946 Издательство: Gazelle Book Services Рейтинг: Цена: 42683.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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 Hobermans 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 modelling 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, artefact 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. Recognise 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.
Автор: Hoberman Steve Название: Data Modeling Made Simple with Powerdesigner ISBN: 0977140091 ISBN-13(EAN): 9780977140091 Издательство: Gazelle Book Services Рейтинг: Цена: 17587.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Data Modeling Made Simple with PowerDesigner 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 PowerDesigner. You'll build many PowerDesigner data models along the way, increasing your skills first with the fundamentals and later with more advanced feature of PowerDesigner. This book combines real-world experience and best practices to help you master the following ten objectives:
This book has ten key objectives for you, the reader:
You will know when a data model is needed and which PowerDesigner models are the most appropriate for each situation
You will be able to read a data model of any size and complexity with the same confidence as reading a book
You will know when to apply and how to make use of all the key features of PowerDesigner
You will be able to build, step-by-step in PowerDesigner, a pyramid of linked data models, including a conceptual data model, a fully normalized relational data model, a physical data model, and an easily navigable dimensional model
You will be able to apply techniques such as indexing, transforms, and forward engineering to turn a logical data model into an efficient physical design
You will improve data governance and modeling consistency within your organization by leveraging features such as PowerDesigner's reference models, Glossary, domains, and model comparison and model mapping techniques
You will know how to utilize dependencies and traceability links to assess the impact of change
You will know how to integrate your PowerDesigner models with externally-managed files, including the import and export of data using Excel and Requirements documents
You will know where you can take advantage of the entire PowerDesigner model set, to increase the success rate of corporate-wide initiatives such as business intelligence and enterprise resource planning (ERP)
You will understand the key differentiators between PowerDesigner and other data modeling tools you may have used before
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