Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Data integration (Computer science)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The worldwide rapid spread and severity of the infectious disease caused by Coronavirus forced the WHO to declare a global state of pandemic emergency during March 2020, by leading the governments around the world to adopt policies that created the widest rift of education systems in human history. Italy have temporarily closed each educational institution, by causing the disruption of tertiary education for 16.89% of the Italian learner's population. To ensure the "pedagogic continuity", universities adopted the transitioning from traditional face-to-face to online learning. This paradigm shift to fully remote teaching solutions represents the so-called emergency remote teaching (ERT) in contrast to the traditional teaching inspired by Bologna process principles such as teaching quality and student satisfaction. In a landscape of emerging difficulties connected to ERT contexts, the quality assurance of higher education recalled by the Bologna Process may be not appropriate. We propose an evaluation model for the quality and ERT success across two dimensions used as proxy variables: students' engagement (SE) and success performance (SP). Within the faculties, we analysed the performance and hence the knowledge, skills and/or attitudes acquired by learners, within the students, the focus was the engagement as interest, motivation and involvement. Under this perspective our research question has an explorative nature: we are interested in detecting empirical evidence about the learning assessment and engagement in higher education with focus on students' engagement and their success performance during ERT. The investigation carried out on Iulm University's student population (N=775). We integrated textual data related to the students evaluation of ERT and their career data such as credits, marks before and post disease. The results show the relations between the two dimensions taken into account, with a multidimensional approach we created a factorial plan useful to create an agile tool of analysis in the ERT context.

Data integration (Computer Science)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Learn the essentials of data integration with this comprehensive guide, covering everything from sources to solutions, and discover the key to making the most of your data stack Key Features Learn how to leverage modern data stack tools and technologies for effective data integration Design and implement data integration solutions with practical advice and best practices Focus on modern technologies such as cloud-based architectures, real-time data processing, and open-source tools and technologies Purchase of the print or Kindle book includes a free PDF eBook Book Description The Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data. This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You'll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you'll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics. By the end of this book, you'll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data. What you will learn Discover the evolving architecture and technologies shaping data integration Process large data volumes efficiently with data warehousing Tackle the complexities of integrating large datasets from diverse sources Harness the power of data warehousing for efficient data storage and processing Design and optimize effective data integration solutions Explore data governance principles and compliance requirements Who this book is for This book is perfect for data engineers, data architects, data analysts, and IT professionals looking to gain a comprehensive understanding of data integration in the modern era. Whether you're a beginner or an experienced professional enhancing your knowledge of the modern data stack, this definitive guide will help you navigate the data integration landscape.

Data integration (Computer science)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Bioinformatics. --- Data integration (Computer Science)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Get to grips with a new technology, understand what it is and what it can do for you, and then get to work with the most important features and tasks.A simple Starter, introducing the Drools concept. The book takes a meticulous approach to providing quick and simple solutions in a practical manner for rules engines and their uses.This book is great for developers, architects, and managers who need to evaluate or get up to speed with Drools engine usage and functionality. This book teaches you to capture and document business processes and represent their maintenance development to business use

Database management. --- Data integration (Computer science)