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Relational Databases and Microsoft Access
Ron McFadyen · University of Winnipeg
Có trong mục lục: 01: Relational Databases and MS Access · 1.01: Relational Databases
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Relational Databases and Microsoft Access 365
Ron McFadyen · Ron McFadyen · 2021
This text is a free introductory text that introduces MS Access and relational database design. The motivation is to support an introductory database system course which, to the student, is either a service course providing an introduction to database concepts, or, as a prerequisite for more advanced study in the field.
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Library 1600: Introduction to College-Level Research
Library Instruction Services · Iowa State University
Có trong mục lục: 2.08: Articles and Databases
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GIS Commons: An Introductory Textbook on Geographic Information Systems
Michael Schmandt · Sacramento State University
This e-text focuses primarily on Geographic Information Systems (GIS)—a geospatial technology that enables you to create spatial databases, analyze spatial patterns, and produce maps that communicate more effectively. While this GIS textbook is principally an introduction to GIS, most of the chapter’s concepts are applicable to other geotechnologies including remote sensing, global positioning systems (GPS), Internet mapping, and virtual globes.
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Introduction to College-level Research
Iowa State University Library Instruction Services · LibreTexts
Có trong mục lục: 2.09: Article indexes and databases
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Library Research Skills for First Year Seminar Students
Kara Blizzard · University of Alberta
This series of modules introduces students to library services and introductory research skills, including finding specific books and articles, choosing a research topic, searching for information using library databases, and citing information sources.
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Library 160: Introduction to College-Level Research
Iowa State University Library Instruction Services · Iowa State University · 2021
You will learn how scholarly information is produced, organized, and accessed; how to construct and use effective search strategies in a variety of web tools and scholarly databases; how to choose finding tools appropriate to the type of information you need; critical thinking skills in the evaluation of resources; and best practices in the ethical use of information.
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A Tale of Two Systems
René Reitsma; Kevin Krueger · Oregon State University · 2017
This is the story of a web-based information system rebuild. The system in question is www.teachengineering.org, a digital library of K-12 engineering curriculum that was built from the ground up with established technology and which for 13 years enjoyed lasting support from its growing user community and its sponsors. These 13 years, however, cover the period during which smart phones and tablets became commonplace, during which the Internet of Things started replacing the Semantic Web, during which NoSQL databases made their way out of the research labs and into everyday development shops, during which we collectively started moving IT functions and services into ‘the cloud,’ and during which computing performance doubled a few times, yet again. During this same period, TeachEngineering’s user base grew from a few hundred to more than 3 million users annually, its collection size quadrupled, it went through several user interface renewals, and significant functionality was added while having an exemplary service record, and it enjoyed continued financial support from its sponsors. In this monograph we provide a side-by-side of this rebuild. We lay out the choices made in the old architecture —we refer to it as TE 1.0— and compare and contrast them with the choices made for TE 2.0. We explain why both the 1.0 and 2.0 choices were made and discuss the advantages and disadvantages associated with them.
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Discrete Mathematics for Information Technology
Simon Crothers · Kwantlen Polytechnic University · 2026
Discrete Mathematics for Information Technology is an applied, student-focused introduction to the mathematical foundations that underpin modern computing. Designed for learners in information technology and business contexts, this textbook bridges theory and practice by connecting core concepts, such as number systems, data representation, logic, proofs, relations, algorithms, Boolean algebra, and graph theory, to real-world applications in programming, networking, databases, and systems design. Each chapter is structured with clear explanations, worked examples, case studies, and programming-oriented exercises that reinforce both conceptual understanding and practical skills. Emphasis is placed on developing analytical thinking, problem-solving, and the ability to model and reason about digital systems with precision and confidence. As an open educational resource, the text is adaptable and accessible, supporting a wide range of teaching and learning environments. By integrating mathematical rigor with authentic IT scenarios, this book equips students with the essential tools needed to succeed in modern, data-driven and technology-focused careers.
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Operating Systems and Infrastructure in Data Science
Josef Spillner · vdf Hochschulverlag · 2023
Modern data scientists work with a number of tools and operating system facilities in addition to online platforms. Mastering these in combination to manage their data and to deploy software, models and data as ready-to-use online services as well as to perform data science and analysis tasks is in the focus of Operating Systems and Infrastructure in Data Science. Readers will come to understand the fundamental concepts of operating systems and to explore plenty of tools in hands-on tasks and thus gradually develop the skills necessary to compose them for programming in the large, an essential capability in their later career. The book guides students through semester studies, acts as reference knowledge base and aids in acquiring the necessary knowledge, skills and competences especially in self-study settings. A unique feature of the book is the associated access to Edushell, a live environment to practice operating systems and infrastructure tasks.
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Research Data Management in the Canadian Context
Emily Carlisle-Johnston; Danielle Dennie; Émilie Fortin; Elizabeth Hill · Western University · 2023
Research Data Management is a term for all the things that researchers do to structure, organize and maintain data before, during and after doing research. RDM is also an emerging discipline that is concerned with researching and developing ways to manage research data more effectively. But what is research data? Where is the push towards formal Research Data Management coming from? What are the requirements of good data management? Research Data Management in the Canadian Context: A Guide for Practitioners and Learners looks at these questions and more, all with a focus on Canadian guidelines, regulations and infrastructure.
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Programming Persistent Memory: A Comprehensive Guide for Developers
Stteve Scargall · Apress · 2020
Beginning and experienced programmers will use this comprehensive guide to persistent memory programming. You will understand how persistent memory brings together several new software/hardware requirements, and offers great promise for better performance and faster application startup times—a huge leap forward in byte-addressable capacity compared with current DRAM offerings. This revolutionary new technology gives applications significant performance and capacity improvements over existing technologies. It requires a new way of thinking and developing, which makes this highly disruptive to the IT/computing industry. The full spectrum of industry sectors that will benefit from this technology include, but are not limited to, in-memory and traditional databases, AI, analytics, HPC, virtualization, and big data. Programming Persistent Memory describes the technology and why it is exciting the industry. It covers the operating system and hardware requirements as well as how to create development environments using emulated or real persistent memory hardware. The book explains fundamental concepts; provides an introduction to persistent memory programming APIs for C, C++, JavaScript, and other languages; discusses RMDA with persistent memory; reviews security features; and presents many examples. Source code and examples that you can run on your own systems are included. What You’ll Learn Understand what persistent memory is, what it does, and the value it brings to the industry Become familiar with the operating system and hardware requirements to use persistent memory Know the fundamentals of persistent memory programming: why it is different from current programming methods, and what developers need to keep in mind when programming for persistence Look at persistent memory application development by example using the Persistent Memory Development Kit (PMDK) Design and optimize data structures for persistent memory Study how real-world applications are modified to le
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Evidence-based Software Engineering
Derek Jones · Knowledge Software · 2020
This book discusses what is currently known about software engineering, based on an analysis of all the publicly available data. This aim is not as ambitious as it sounds, because there is not a great deal of data publicly available. The intent is to provide material that is useful to professional developers working in industry; until recently researchers in software engineering have been more interested in vanity work, promoted by ego and bluster. The material is organized in two parts, the first covering software engineering and the second the statistics likely to be needed for the analysis of software engineering data.
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The Crystal Ball Instruction Manual
Stephen Davies · University of Mary Washington · 2020
A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background.
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The Discipline of Organizing: 4th Professional Edition
Robert Glushko · University of California, Berkeley · 2013
We organize things, we organize information, we organize information about things, and we organize information about information. But even though “organizing” is a fundamental and ubiquitous challenge, when we compare these activities their contrasts are more apparent than their commonalities. We propose to unify many perspectives about organizing with the concept of an Organizing System, defined as an intentionally arranged collection of resources and the interactions they support. Every Organizing System involves a collection of resources, a choice of properties or principles used to describe and arrange resources, and ways of supporting interactions with resources. By comparing and contrasting how these activities take place in different contexts and domains, we can identify patterns of organizing. We can create a discipline of organizing in a disciplined way. The 4th edition builds a bridge between organizing and data science. It reframes descriptive statistics as organizing techniques, expands the treatment of classification to include computational methods, and incorporates many new examples of data-driven resource selection, organization, maintenance, and personalization. It introduces a new “data science” category of discipline-specific content, both in the chapter text and in endnotes, marked with [DS] in editions that contain endnotes.
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Enterprise Pharo a Web Perspective
Square Bracket Associates · 2016
Enterprise Pharo is the third volume of the series, following Pharo by Example and Deep into Pharo. It covers enterprise libraries and frameworks, and in particular those useful for doing web development. The book is structured in five parts. The first part talks about simple web applications, starting with a minimal web application in chapter 1 on Teapot and then a tutorial on building a more complete web application in chapter 2. Part two deals with HTTP support in Pharo, talking about character encoding in chapter 3, about using Pharo as an HTTP Client (chapter 4) and server (chapter 5), and about using WebSockets (chapter 6).In the third part we discuss the handling of data for the application. Firstly we treat data that is in the form of comma-separated values (CSV) in chapter 7. Secondly and thirdly, we treat JSON (chapter 8) and its Smalltalk counterpart STON (chapter 9). Fourthly, serialization and deserialization of object graphs with Fuel is treated in chapter 10. Lastly, we discuss the Voyage persistence framework and persisting to MongoDB databases in chapter 11. Part four deals with the presentation layer. Chapter 12 shows how to use Mustache templates in Pharo, and chapter 13 talks about programmatic generationof CSS files. The documentation of applications could be written in Pillar, which is presented in chapter 14. How to generate PDF files from the application with Artefact is shown in chapter 15. The fifth part deals with deploying the web application. This is explained in chapter 16 that talks not only about how to build and run the application, but also other important topics like monitoring.
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Database Design
Adrienne Watt · BCcampus · 2014
This second edition of Database Design book covers the concepts used in database systems and the database design process. Topics include: The history of databases Characteristics and benefits of databases Data models Data modelling Classification of database management systems Integrity rules and constraints Functional dependencies Normalization Database development process New to this edition are more examples, highlighted and defined key terms, both throughout and at the end of each chapter, and end-of-chapter review exercises. Two new chapters have been added on SQL, along with appendices that include a data model example, sample ERD exercises and SQL lab with solutions.
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Python for Everybody: Exploring Data Using Python 3
Charles Severance · Charles Severance · 2016
I never seemed to find the perfect data-oriented Python book for my course, so I set out to write just such a book. Luckily at a faculty meeting three weeks before I was about to start my new book from scratch over the holiday break, Dr. Atul Prakash showed me the Think Python book which he had used to teach his Python course that semester. It is a well-written Computer Science text with a focus on short, direct explanations and ease of learning.The overall book structure has been changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis from the very beginning. Chapters 2–10 are similar to the Think Python book, but there have been major changes. Number-oriented examples and exercises have been replaced with data- oriented exercises. Topics are presented in the order needed to build increasingly sophisticated data analysis solutions. Some topics like try and except are pulled forward and presented as part of the chapter on conditionals. Functions are given very light treatment until they are needed to handle program complexity rather than introduced as an early lesson in abstraction. Nearly all user-defined functions have been removed from the example code and exercises outside of Chapter 4. The word “recursion”1 does not appear in the book at all. In chapters 1 and 11–16, all of the material is brand new, focusing on real-world uses and simple examples of Python for data analysis including regular expressions for searching and parsing, automating tasks on your computer, retrieving data across the network, scraping web pages for data, object-oriented programming, using web services, parsing XML and JSON data, creating and using databases using Structured Query Language, and visualizing data. The ultimate goal of all of these changes is a shift from a Computer Science to an Informatics focus is to only include topics into a first technology class that can be useful even if one choose
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Choosing and Using Sources - A Guide to Academic Resear
Cheryl Lowry · The Ohio State University
Có trong mục lục: 5.04: Specialized Databases
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Information Systems for Business
Ly-Huong T. Pham, Tejal Desai-Naik, Laurie Hammond, & Wael Abdeljabbar · OERI
Có trong mục lục: 04: Data and Databases · 4.01: Introduction to Data and Databases · 4.10: Enterprise Databases