Data Models And Analysis
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Data Analysis Data Modeling And Classification
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Author : Martin E. Modell
language : en
Publisher: McGraw-Hill Companies
Release Date : 1992
Data Analysis Data Modeling And Classification written by Martin E. Modell and has been published by McGraw-Hill Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Computers categories.
From a widely published, international expert in both the theory and practical applications of the entity-relationship approach, this reference takes the reader from data entity analysis at the enterprise level through data element analysis and physical design considerations.
Developing High Quality Data Models
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Author : Matthew West
language : en
Publisher: Elsevier
Release Date : 2011-02-07
Developing High Quality Data Models written by Matthew West and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-07 with Computers categories.
Developing High Quality Data Models provides an introduction to the key principles of data modeling. It explains the purpose of data models in both developing an Enterprise Architecture and in supporting Information Quality; common problems in data model development; and how to develop high quality data models, in particular conceptual, integration, and enterprise data models. The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data models in enterprise architecture. Part 2 introduces some general principles for data models, including principles for developing ontologically based data models; and applications of the principles for attributes, relationship types, and entity types. Part 3 presents an ontological framework for developing consistent data models. Part 4 provides the full data model that has been in development throughout the book. The model was created using Jotne EPM Technologys EDMVisualExpress data modeling tool. This book was designed for all types of modelers: from those who understand data modeling basics but are just starting to learn about data modeling in practice, through to experienced data modelers seeking to expand their knowledge and skills and solve some of the more challenging problems of data modeling. Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templates Develops ideas for creating consistent approaches to high quality data models
Advances In Complex Data Modeling And Computational Methods In Statistics
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Author : Anna Maria Paganoni
language : en
Publisher: Springer
Release Date : 2014-11-04
Advances In Complex Data Modeling And Computational Methods In Statistics written by Anna Maria Paganoni and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-04 with Mathematics categories.
The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.
Data Models And Statistical Analysis
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Author : Ron A. Cooper
language : en
Publisher: Rowman & Littlefield Publishers
Release Date : 1983
Data Models And Statistical Analysis written by Ron A. Cooper and has been published by Rowman & Littlefield Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Mathematics categories.
This intermediate-level statistics text is directed to the analysis of nonexperimental data of the kind found in economics and business studies, sociology, geography, and the behavioral sciences. In addition to the areas usually covered in texts at this level (i.e., univariate and bivariate analysis and multiple regression), the authors have included an introduction to topics of considerable practical utility that are usually considered beyond intermediate level. These include various multivariate methods and the analysis of the multiway contingency tables. The authors have also included, in a practical setting, the use of some distributions, such as the lognormal and the negative binomial.
Mastering Data Modeling
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Author : John Vincent Carlis
language : en
Publisher: Addison-Wesley Professional
Release Date : 2001
Mastering Data Modeling written by John Vincent 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 2001 with Computers categories.
Carlis (computer science, U. of Minnesota) and Maguire a program manager for Microsoft, explain to information systems analysts and database developers how to become a successful data modeler. Using their own Logical Data Structure for the data modeling notation, they describe in detail the process for collecting, modeling, and documenting data structures and flow. They also analyze all data shapes and provide several recipes for applying them. They provide no bibliographic references. Annotation copyrighted by Book News, Inc., Portland, OR
Expert Data Modeling With Power Bi
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Author : Soheil Bakhshi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-06-11
Expert Data Modeling With Power Bi written by Soheil Bakhshi 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 2021-06-11 with Computers categories.
Manage and work with business data effectively by learning data modeling techniques and leveraging the latest features of Power BI Key Features Understand data modeling techniques to get the best out of data using Power BI Define the relationships between data to extract valuable insights Solve a wide variety of business challenges by building optimal data models Book DescriptionThis book is a comprehensive guide to understanding the ins and outs of data modeling and how to create data models using Power BI confidently. You'll learn how to connect data from multiple sources, understand data, define and manage relationships between data, and shape data models to gain deep and detailed insights about your organization. In this book, you'll explore how to use data modeling and navigation techniques to define relationships and create a data model before defining new metrics and performing custom calculations using modeling features. As you advance through the chapters, the book will demonstrate how to create full-fledged data models, enabling you to create efficient data models and simpler DAX code with new data modeling features. With the help of examples, you'll discover how you can solve business challenges by building optimal data models and changing your existing data models to meet evolving business requirements. Finally, you'll learn how to use some new and advanced modeling features to enhance your data models to carry out a wide variety of complex tasks. By the end of this Power BI book, you'll have gained the skills you need to structure data coming from multiple sources in different ways to create optimized data models that support reporting and data analytics.What you will learn Implement virtual tables and time intelligence functionalities in DAX to build a powerful model Identify Dimension and Fact tables and implement them in Power Query Editor Deal with advanced data preparation scenarios while building Star Schema Explore best practices for data preparation and modeling Discover different hierarchies and their common pitfalls Understand complex data models and how to decrease the level of model complexity with different approaches Learn advanced data modeling techniques such as aggregations, incremental refresh, and RLS/OLS Who this book is for This MS Power BI book is for BI users, data analysts, and analysis developers who want to become well-versed with data modeling techniques to make the most of Power BI. You’ll need a solid grasp on basic use cases and functionalities of Power BI and Star Schema functionality before you can dive in.
Lifetime Data Models In Reliability And Survival Analysis
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Author : Nicholas P. Jewell
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Lifetime Data Models In Reliability And Survival Analysis written by Nicholas P. Jewell and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Mathematics categories.
Statistical models and methods for lifetime and other time-to-event data are widely used in many fields, including medicine, the environmental sciences, actuarial science, engineering, economics, management, and the social sciences. For example, closely related statistical methods have been applied to the study of the incubation period of diseases such as AIDS, the remission time of cancers, life tables, the time-to-failure of engineering systems, employment duration, and the length of marriages. This volume contains a selection of papers based on the 1994 International Research Conference on Lifetime Data Models in Reliability and Survival Analysis, held at Harvard University. The conference brought together a varied group of researchers and practitioners to advance and promote statistical science in the many fields that deal with lifetime and other time-to-event-data. The volume illustrates the depth and diversity of the field. A few of the authors have published their conference presentations in the new journal Lifetime Data Analysis (Kluwer Academic Publishers).
Hierarchical Modeling And Analysis For Spatial Data
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Author : Sudipto Banerjee
language : en
Publisher: CRC Press
Release Date : 2014-09-12
Hierarchical Modeling And Analysis For Spatial Data written by Sudipto Banerjee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-12 with Mathematics categories.
Keep Up to Date with the Evolving Landscape of Space and Space-Time Data Analysis and ModelingSince the publication of the first edition, the statistical landscape has substantially changed for analyzing space and space-time data. More than twice the size of its predecessor, Hierarchical Modeling and Analysis for Spatial Data, Second Edition reflec
Grade Models And Methods For Data Analysis
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Author : Teresa Kowalczyk
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-04-16
Grade Models And Methods For Data Analysis written by Teresa Kowalczyk and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-16 with Computers categories.
This book provides a new grade methodology for intelligent data analysis. It introduces a specific infrastructure of concepts needed to describe data analysis models and methods. This monograph is the only book presently available covering both the theory and application of grade data analysis and therefore aiming both at researchers, students, as well as applied practitioners. The text is richly illustrated through examples and case studies and includes a short introduction to software implementing grade methods, which can be downloaded from the editors.
Hands On Big Data Modeling
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Author : James Lee
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-30
Hands On Big Data Modeling written by James Lee 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 2018-11-30 with Computers categories.
Solve all big data problems by learning how to create efficient data models Key FeaturesCreate effective models that get the most out of big dataApply your knowledge to datasets from Twitter and weather data to learn big dataTackle different data modeling challenges with expert techniques presented in this bookBook Description Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements. To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently. What you will learnGet insights into big data and discover various data modelsExplore conceptual, logical, and big data modelsUnderstand how to model data containing different file typesRun through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modelingCreate data models such as Graph Data and Vector SpaceModel structured and unstructured data using Python and RWho this book is for This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.