Data Modeling, A Beginner's Guide
Data Modeling, A Beginner's Guide

Author: Andy Oppel

Publisher: McGraw Hill Professional

Published: 2009-11-23

Total Pages: 366

ISBN-13: 007162399X

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Essential Skills--Made Easy! Learn how to create data models that allow complex data to be analyzed, manipulated, extracted, and reported upon accurately. Data Modeling: A Beginner's Guide teaches you techniques for gathering business requirements and using them to produce conceptual, logical, and physical database designs. You'll get details on Unified Modeling Language (UML), normalization, incorporating business rules, handling temporal data, and analytical database design. The methods presented in this fast-paced tutorial are applicable to any database management system, regardless of vendor. Designed for Easy Learning Key Skills & Concepts--Chapter-opening lists of specific skills covered in the chapter Ask the expert--Q&A sections filled with bonus information and helpful tips Try This--Hands-on exercises that show you how to apply your skills Notes--Extra information related to the topic being covered Self Tests--Chapter-ending quizzes to test your knowledge Andy Oppel has taught database technology for the University of California Extension for more than 25 years. He is the author of Databases Demystified, SQL Demystified, and Databases: A Beginner's Guide, and the co-author of SQL: A Beginner's Guide, Third Edition, and SQL: The Complete Reference, Third Edition.

Databases A Beginner's Guide
Databases A Beginner's Guide

Author: Andy Oppel

Publisher: McGraw Hill Professional

Published: 2009-05-31

Total Pages: 497

ISBN-13: 0071608478

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Essential Database Skills--Made Easy! Learn standard database design and management techniques applicable to any type of database. Featuring clear examples using both Microsoft Access and Oracle, Databases: A Beginner's Guide begins by showing you how to use Structured Query Language (SQL) to create and access database objects. Then, you'll discover how to implement logical design using normalization, transform the logical design into a physical database, and handle data and process modeling. You'll also get details on database security, online analytical processing (OLAP), connecting databases to applications, and integrating XML and object content into databases. Designed for Easy Learning Key Skills & Concepts--Chapter-opening lists of specific skills covered in the chapter Ask the Expert--Q&A sections filled with bonus information and helpful tips Try This--Hands-on exercises that show you how to apply your skills Notes--Extra information related to the topic being covered Self Tests--Chapter-ending quizzes to test your knowledge

SQL for Data Scientists
SQL for Data Scientists

Author: Renee M. P. Teate

Publisher: John Wiley & Sons

Published: 2021-08-17

Total Pages: 400

ISBN-13: 1119669391

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Jump-start your career as a data scientist—learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that’s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. This guide for data scientists differs from other instructional guides on the subject. It doesn’t cover SQL broadly. Instead, you’ll learn the subset of SQL skills that data analysts and data scientists use frequently. You’ll also gain practical advice and direction on "how to think about constructing your dataset." Gain an understanding of relational database structure, query design, and SQL syntax Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms Review strategies and approaches so you can design analytical datasets Practice your techniques with the provided database and SQL code In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner’s perspective, moving your data scientist career forward!

A Beginner's Guide to Structural Equation Modeling
A Beginner's Guide to Structural Equation Modeling

Author: Randall E. Schumacker

Publisher: Psychology Press

Published: 2004-06-24

Total Pages: 590

ISBN-13: 1135641919

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The second edition features: a CD with all of the book's Amos, EQS, and LISREL programs and data sets; new chapters on importing data issues related to data editing and on how to report research; an updated introduction to matrix notation and programs that illustrate how to compute these calculations; many more computer program examples and chapter exercises; and increased coverage of factors that affect correlation, the 4-step approach to SEM and hypothesis testing, significance, power, and sample size issues. The new edition's expanded use of applications make this book ideal for advanced students and researchers in psychology, education, business, health care, political science, sociology, and biology. A basic understanding of correlation is assumed and an understanding of the matrices used in SEM models is encouraged.

Data Modeling Essentials
Data Modeling Essentials

Author: Graeme Simsion

Publisher: Elsevier

Published: 2004-12-03

Total Pages: 561

ISBN-13: 0080488676

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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

A Developer's Guide to Data Modeling for SQL Server
A Developer's Guide to Data Modeling for SQL Server

Author: Eric Johnson

Publisher: Addison-Wesley Professional

Published: 2008-06-24

Total Pages: 445

ISBN-13: 0132701537

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“ A Developer’s Guide to Data Modeling for SQL Server explains the concepts and practice of data modeling with a clarity that makes the technology accessible to anyone building databases and data-driven applications. “Eric Johnson and Joshua Jones combine a deep understanding of the science of data modeling with the art that comes with years of experience. If you’re new to data modeling, or find the need to brush up on its concepts, this book is for you.” — Peter Varhol, Executive Editor, Redmond Magazine Model SQL Server Databases That Work Better, Do More, and Evolve More Smoothly Effective data modeling is essential to ensuring that your databases will perform well, scale well, and evolve to meet changing requirements. However, if you’re modeling databases to run on Microsoft SQL Server 2008 or 2005, theoretical or platform-agnostic data modeling knowledge isn’t enough: models that don’t reflect SQL Server’s unique real-world strengths and weaknesses often lead to disastrous performance. A Developer’s Guide to Data Modeling for SQL Server is a practical, SQL Server-specific guide to data modeling for every developer, architect, and administrator. This book offers you invaluable start-to-finish guidance for designing new databases, redesigning existing SQL Server data models, and migrating databases from other platforms. You’ll begin with a concise, practical overview of the core data modeling techniques. Next, you’ll walk through requirements gathering and discover how to convert requirements into effective SQL Server logical models. Finally, you’ll systematically transform those logical models into physical models that make the most of SQL Server’s extended functionality. All of this book’s many examples are available for download from a companion Web site. This book enables you to Understand your data model’s physical elements, from storage to referential integrity Provide programmability via stored procedures, user-defined functions, triggers, and .NET CLR integration Normalize data models, one step at a time Gather and interpret requirements more effectively Learn an effective methodology for creating logical models Overcome modeling problems related to entities, attribute, data types, storage overhead, performance, and relationships Create physical models—from establishing naming guidelines through implementing business rules and constraints Use SQL Server’s unique indexing capabilities, and overcome their limitations Create abstraction layers that enhance security, extensibility, and flexibility

R for Data Science
R for Data Science

Author: Hadley Wickham

Publisher: "O'Reilly Media, Inc."

Published: 2016-12-12

Total Pages: 521

ISBN-13: 1491910364

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Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

The Data Model Resource Book, Volume 1
The Data Model Resource Book, Volume 1

Author: Len Silverston

Publisher: John Wiley & Sons

Published: 2011-08-08

Total Pages: 572

ISBN-13: 111808232X

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A quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful 1st Edition, while adding a companion volume to take care of more specific requirements of different businesses. This updated volume provides a common set of data models for specific core functions shared by most businesses like human resources management, accounting, and project management. These models are standardized and are easily replicated by developers looking for ways to make corporate database development more efficient and cost effective. This guide is the perfect complement to The Data Model Resource CD-ROM, which is sold separately and provides the powerful design templates discussed in the book in a ready-to-use electronic format. A free demonstration CD-ROM is available with each copy of the print book to allow you to try before you buy the full CD-ROM.

MySQL Workbench: Data Modeling & Development
MySQL Workbench: Data Modeling & Development

Author: Michael McLaughlin

Publisher: McGraw Hill Professional

Published: 2013-05-06

Total Pages: 481

ISBN-13: 0071791892

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The only Oracle Press guide to MySQL Workbench explains how to design and model MySQL databases. MySQL Workbench Data Modeling and Development helps developers learn how to effectively use this powerful product for database modeling, reverse engineering, and interaction with the database without writing SQL statements. MySQL Workbench is a graphical user interface that can be used to create and maintain MySQL databases without coding. The book covers the interface and explains how to accomplish each step by illustrating best practices visually. Clear examples, instructions, and explanations reveal, in a single volume, the art of database modeling. This Oracle Press guide shows you how to get the tool to do what you want. Annotated screen shots demonstrate all interactions with the tool, and text explains the how, what, and why of each step. Complete coverage Installation and Configuration; Creating and Managing Connections; Data Modeling Concepts; Creating an ERD; Defining the Physical Schemata; Creating and Managing Tables; Creating and Managing Relationships; Creating and Managing Views; Creating and Managing Routines; Creating and Managing Routine Groups; Creating and Managing User & Groups; Creating and Managing SQL Scripts; Generating SQL Scripts; Forward Engineering a Data Model; Synchronize a Model with a Database; Reverse Engineering a Database; Managing Differences in the Data Catalog; Creating and Managing Model Notes; Editing Table Data; Editing Generated Scripts; Creating New Instances; Managing Import and Export; Managing Security; Managing Server Instances

Mobility Data
Mobility Data

Author: Chiara Renso

Publisher: Cambridge University Press

Published: 2013-10-14

Total Pages: 393

ISBN-13: 1107292360

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Mobility of people and goods is essential in the global economy. The ability to track the routes and patterns associated with this mobility offers unprecedented opportunities for developing new, smarter applications in different domains. Much of the current research is devoted to developing concepts, models, and tools to comprehend mobility data and make it manageable for these applications. This book surveys the myriad facets of mobility data, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis, with a specific focus on monitoring people in motion (drivers, airplane passengers, crowds, and even animals in the wild). Written by a renowned group of worldwide experts, it presents a consistent framework that facilitates understanding of all these different facets, from basic definitions to state-of-the-art concepts and techniques, offering both researchers and professionals a thorough understanding of the applications and opportunities made possible by the development of mobility data.