Database Design - 2nd Edition
Copyright Year:
Contributor: Watt
Publisher: BCcampus
License: CC BY
This second edition of Database Design book covers the concepts used in database systems and the database design process. Topics include:
(15 reviews)
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Relational Databases and Microsoft Access 365 - Version 4.0
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Contributor: McFadyen
Publisher: Ron McFadyen
License: CC BY-NC-SA
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.
(8 reviews)
The Discipline of Organizing: 4th Professional Edition
Copyright Year:
Contributor: Glushko
Publisher: University of California, Berkeley
License: CC BY-NC
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.
(3 reviews)
The Crystal Ball Instruction Manual - version 1.1 Volume One: Introduction to Data Science
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Contributor: Davies
Publisher: University of Mary Washington
License: CC BY-SA
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.
(3 reviews)
Evidence-based Software Engineering
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Contributor: Jones
Publisher: Knowledge Software
License: CC BY-SA
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.
(1 review)
Research Data Management in the Canadian Context
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Contributors: Carlisle-Johnston, Dennie, Fortin, Hill, and Thompson
Publisher: Western University
License: CC BY-NC
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.
(1 review)
Operating Systems and Infrastructure in Data Science
Copyright Year:
Contributor: Spillner
Publisher: vdf Hochschulverlag
License: CC BY-NC-SA
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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