Mastering Data Modeling
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Mastering Data Modeling
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Author : John Carlis
language : en
Publisher: Addison-Wesley Professional
Release Date : 2000-11-10
Mastering Data Modeling written by John Carlis and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-11-10 with Computers categories.
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.
Mastering Data Modeling
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Author : Michael E. Kirshteyn
language : en
Publisher:
Release Date : 2023-11-22
Mastering Data Modeling written by Michael E. Kirshteyn and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-22 with categories.
Mastering Data Warehouse Design
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Author : Claudia Imhoff
language : en
Publisher: Wiley
Release Date : 2003
Mastering Data Warehouse Design written by Claudia Imhoff and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.
A cutting-edge response to Ralph Kimball's challenge to the data warehouse community that answers some tough questions about the effectiveness of the relational approach to data warehousing Written by one of the best-known exponents of the Bill Inmon approach to data warehousing Addresses head-on the tough issues raised by Kimball and explains how to choose the best modeling technique for solving common data warehouse design problems Weighs the pros and cons of relational vs. dimensional modeling techniques Focuses on tough modeling problems, including creating and maintaining keys and modeling calendars, hierarchies, transactions, and data quality
Data Modeling Master Class Training Manual
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Author : Steve Hoberman
language : en
Publisher:
Release Date : 2015-07
Data Modeling Master Class Training Manual written by Steve Hoberman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07 with categories.
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
Mastering Predictive Analytics With R
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Author : Rui Miguel Forte
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-06-17
Mastering Predictive Analytics With R written by Rui Miguel Forte and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-17 with Computers categories.
R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. This book is designed to be both a guide and a reference for moving beyond the basics of predictive modeling. The book begins with a dedicated chapter on the language of models and the predictive modeling process. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real world data sets. By the end of this book, you will have explored and tested the most popular modeling techniques in use on real world data sets and mastered a diverse range of techniques in predictive analytics.
Mastering Predictive Analytics With R
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Author : James D. Miller
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-08-18
Mastering Predictive Analytics With R written by James D. Miller and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-18 with Computers categories.
Master the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts About This Book Grasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding Leveraging the flexibility and modularity of R to experiment with a range of different techniques and data types Packed with practical advice and tips explaining important concepts and best practices to help you understand quickly and easily Who This Book Is For Although budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced data scientist professional wishing to attain master level status , will also find this book extremely valuable.. This book assumes familiarity with the fundamentals of R, such as the main data types, simple functions, and how to move data around. Although no prior experience with machine learning or predictive modeling is required, there are some advanced topics provided that will require more than novice exposure. What You Will Learn Master the steps involved in the predictive modeling process Grow your expertise in using R and its diverse range of packages Learn how to classify predictive models and distinguish which models are suitable for a particular problem Understand steps for tidying data and improving the performing metrics Recognize the assumptions, strengths, and weaknesses of a predictive model Understand how and why each predictive model works in R Select appropriate metrics to assess the performance of different types of predictive model Explore word embedding and recurrent neural networks in R Train models in R that can work on very large datasets In Detail R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do you train models that can handle really large datasets? This book will also show you just that. Finally, you will tackle the really important topic of deep learning by implementing applications on word embedding and recurrent neural networks. By the end of this book, you will have explored and tested the most popular modeling techniques in use on real- world datasets and mastered a diverse range of techniques in predictive analytics using R. Style and approach This book takes a step-by-step approach in explaining the intermediate to advanced concepts in predictive analytics. Every concept is explained in depth, supplemented with practical examples applicable in a real-world setting.
Power Bi
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Author : Kiet Huynh
language : en
Publisher:
Release Date : 2023-11-07
Power Bi written by Kiet Huynh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-07 with categories.
Welcome to the world of data modeling and analytics in Power BI, where we will embark on a journey of discovery and mastery. In this book, "Power BI: Mastering DAX for Advanced Data Modeling," we will delve deep into the intricacies of the Data Analysis Expressions (DAX) language and explore the advanced techniques needed to harness its full potential. Whether you're a business professional seeking to make data-driven decisions or a data analyst aiming to create powerful data models, this book is your comprehensive guide. We will cover a wide range of topics, from the fundamentals of DAX to advanced data modeling, performance optimization, and case studies in various domains. By the end of this journey, you'll possess the knowledge and skills to tackle complex data challenges and unlock valuable insights for your organization. Our goal is to provide you with a clear, practical, and insightful understanding of DAX and Power BI, enabling you to create data models that drive success. Throughout this book, we'll offer step-by-step explanations, real-world examples, and hands-on exercises to ensure your learning experience is both enjoyable and productive. As the field of data analysis and business intelligence continues to evolve, staying ahead of the curve is essential. "Power BI: Mastering DAX for Advanced Data Modeling" equips you with the tools you need to remain at the forefront of this dynamic industry. We hope you find this book not only informative but also empowering as you unlock the full potential of your data. Thank you for choosing this book to enhance your data modeling skills. Let's embark on this exciting journey together and pave the way for a future filled with data-driven insights.
Data Modeling Master Class Training Manual 5th Edition
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Author : Steve Hoberman
language : en
Publisher: Technics Publications, LLC
Release Date : 2014
Data Modeling Master Class Training Manual 5th Edition written by Steve Hoberman and has been published by Technics Publications, LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Data structures (Computer science) categories.
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 For The Business
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Author : Steve Hoberman
language : en
Publisher: Technics Publications Llc
Release Date : 2009
Data Modeling For The Business written by Steve Hoberman and has been published by Technics Publications Llc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computers categories.
Did you ever try getting Business and IT to agree on the project scope for a new application? Or try getting the Sales & Marketing department to agree on the target audience? Or try bringing new team members up to speed on the hundreds of tables in your data warehouse -- without them dozing off? You can be the hero in each of these and hundreds of other scenarios by building a High-Level Data Model. The High-Level Data Model is a simplified view of our complex environment. It can be a powerful communication tool of the key concepts within our application development projects, business intelligence and master data management programs, and all enterprise and industry initiatives. Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach. Know how to evaluate toolsets for building and storing your models. Practice exercises and walk through a case study to reinforce your modelling skills.
Data Modeling Fundamentals
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Author : Steve Hoberman
language : en
Publisher:
Release Date : 2018
Data Modeling Fundamentals written by Steve Hoberman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
"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.