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This guidebook highlights the process of a software internship
project facilitated by the Schulich School of Engineering. The
Scrum Team is comprised of student developers pursuing either a
master’s or bachelor’s degree in Software Engineering with
their professor as the stakeholder, a consulting tech company
serving as the product owner, and a graduate student and seasoned
industry expert as project leads. The story of this software
development process is communicated through the perspectives of an
observing undergraduate SE student and the team, mainly through
meetings, interviews, and journal entries. This guidebook is for
readers in research, education, and industry who will not only
experience the same process from different angles, but they will
gain insight into fundamental elements of the Scrum Framework
applied in organizational projects.
Data management and analysis is one of the fastest growing and most
challenging areas of research and development in both academia and
industry. Numerous types of applications and services have been
studied and re-examined in this field resulting in this edited
volume which includes chapters on effective approaches for dealing
with the inherent complexity within data management and analysis.
This edited volume contains practical case studies, and will appeal
to students, researchers and professionals working in data
management and analysis in the business, education, healthcare, and
bioinformatics areas.
This book addresses and examines the impacts of applications and
services for data management and analysis, such as infrastructure,
platforms, software, and business processes, on both academia and
industry. The chapters cover effective approaches in dealing with
the inherent complexity and increasing demands of big data
management from an applications perspective. Various case studies
included have been reported by data analysis experts who work
closely with their clients in such fields as education, banking,
and telecommunications. Understanding how data management has been
adapted to these applications will help students, instructors and
professionals in the field. Application areas also include the
fields of social network analysis, bioinformatics, and the oil and
gas industries.
This book addresses and examines the impacts of applications and
services for data management and analysis, such as infrastructure,
platforms, software, and business processes, on both academia and
industry. The chapters cover effective approaches in dealing with
the inherent complexity and increasing demands of big data
management from an applications perspective. Various case studies
included have been reported by data analysis experts who work
closely with their clients in such fields as education, banking,
and telecommunications. Understanding how data management has been
adapted to these applications will help students, instructors and
professionals in the field. Application areas also include the
fields of social network analysis, bioinformatics, and the oil and
gas industries.
This book addresses the impacts of various types of services such
as infrastructure, platforms, software, and business processes that
cloud computing and Big Data have introduced into business.
Featuring chapters which discuss effective and efficient approaches
in dealing with the inherent complexity and increasing demands in
data science, a variety of application domains are covered. Various
case studies by data management and analysis experts are presented
in these chapters. Covered applications include banking, social
networks, bioinformatics, healthcare, transportation and
criminology. Highlighting the Importance of Big Data Management and
Analysis for Various Applications will provide the reader with an
understanding of how data management and analysis are adapted to
these applications. This book will appeal to researchers and
professionals in the field.
Data management and analysis is one of the fastest growing and most
challenging areas of research and development in both academia and
industry. Numerous types of applications and services have been
studied and re-examined in this field resulting in this edited
volume which includes chapters on effective approaches for dealing
with the inherent complexity within data management and analysis.
This edited volume contains practical case studies, and will appeal
to students, researchers and professionals working in data
management and analysis in the business, education, healthcare, and
bioinformatics areas.
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Paperback
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R398
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Discovery Miles 3 300
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