Identification of Big Data Use-cases in Airline Operations
Identification of Big Data Use-cases in Airline Operations

Author: Anna Achenbach

Publisher:

Published: 2015

Total Pages:

ISBN-13:

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The airline industry is one of the most competitive industries in the world. The struggle for market share translates into a high pressure for both commercial and operational functions. In the past operations research has helped airlines to significantly increase their efficiency by applying advanced mathematical models. With big data new developments in the area of data analytics are expected. The airline industry is just now catching on to this innovative trend. Few use-cases are implemented as of today, but the value big data analytics can deliver, has been shown in many other industries such as the retail industry and the financial sector. Within the airline industry there is a strong interest in investigating the possible benefits and applications of big data analytics both for commercial and operational functions. With the focus on airline operations this thesis aims at providing a detailed overview of the current status of big data analytics as well as identifying future areas for big data analytics in airline operations. A literature review and ten expert interviews make up the basis for this study.The results of the study show the importance and relevance of the topic in today`s airline industry. All experts were in unison saying that big data will be a critical asset for airline operations. As of today there are several use-cases of big data analytics in place, but only very few have passed the piloting stage. Considering both the insights gained in the literature review and during the expert interviews the following areas of airline operations are regarded most promising for future research: predictive maintenance, fuel efficiency, crew scheduling and delay prediction. Overall there is a very high interest in this field and further research should be conducted.

Information Governance Principles and Practices for a Big Data Landscape
Information Governance Principles and Practices for a Big Data Landscape

Author: Chuck Ballard

Publisher: IBM Redbooks

Published: 2014-03-31

Total Pages: 280

ISBN-13: 0738439592

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This IBM® Redbooks® publication describes how the IBM Big Data Platform provides the integrated capabilities that are required for the adoption of Information Governance in the big data landscape. As organizations embark on new use cases, such as Big Data Exploration, an enhanced 360 view of customers, or Data Warehouse modernization, and absorb ever growing volumes and variety of data with accelerating velocity, the principles and practices of Information Governance become ever more critical to ensure trust in data and help organizations overcome the inherent risks and achieve the wanted value. The introduction of big data changes the information landscape. Data arrives faster than humans can react to it, and issues can quickly escalate into significant events. The variety of data now poses new privacy and security risks. The high volume of information in all places makes it harder to find where these issues, risks, and even useful information to drive new value and revenue are. Information Governance provides an organization with a framework that can align their wanted outcomes with their strategic management principles, the people who can implement those principles, and the architecture and platform that are needed to support the big data use cases. The IBM Big Data Platform, coupled with a framework for Information Governance, provides an approach to build, manage, and gain significant value from the big data landscape.

Big Data Analytics: Systems, Algorithms, Applications
Big Data Analytics: Systems, Algorithms, Applications

Author: C.S.R. Prabhu

Publisher: Springer Nature

Published: 2019-10-14

Total Pages: 412

ISBN-13: 9811500940

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This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

Big Data to Improve Strategic Network Planning in Airlines
Big Data to Improve Strategic Network Planning in Airlines

Author: Maximilian Schosser

Publisher: Springer Nature

Published: 2019-09-05

Total Pages: 462

ISBN-13: 3658275820

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Big data has become an important success driver in airline network planning. Maximilian Schosser explores the status quo of network planning across a case study group consisting of nine airlines representing different business models. The author describes 23 big data opportunities for airline network planning and evaluates them based on their specific value contribution for airline network planning. Subsequently, he develops a financial evaluation methodology for big data opportunities based on key performance indicators for airline network planning departments.

Encyclopedia of Information Systems and Technology - Two Volume Set
Encyclopedia of Information Systems and Technology - Two Volume Set

Author: Phillip A. Laplante

Publisher: CRC Press

Published: 2015-12-29

Total Pages: 1307

ISBN-13: 1482214326

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Spanning the multi-disciplinary scope of information technology, the Encyclopedia of Information Systems and Technology draws together comprehensive coverage of the inter-related aspects of information systems and technology. The topics covered in this encyclopedia encompass internationally recognized bodies of knowledge, including those of The IT BOK, the Chartered Information Technology Professionals Program, the International IT Professional Practice Program (British Computer Society), the Core Body of Knowledge for IT Professionals (Australian Computer Society), the International Computer Driving License Foundation (European Computer Driving License Foundation), and the Guide to the Software Engineering Body of Knowledge. Using the universally recognized definitions of IT and information systems from these recognized bodies of knowledge, the encyclopedia brings together the information that students, practicing professionals, researchers, and academicians need to keep their knowledge up to date. Also Available Online This Taylor & Francis encyclopedia is also available through online subscription, offering a variety of extra benefits for researchers, students, and librarians, including:  Citation tracking and alerts  Active reference linking  Saved searches and marked lists  HTML and PDF format options Contact Taylor and Francis for more information or to inquire about subscription options and print/online combination packages. US: (Tel) 1.888.318.2367; (E-mail) [email protected] International: (Tel) +44 (0) 20 7017 6062; (E-mail) [email protected]

HBase: The Definitive Guide
HBase: The Definitive Guide

Author: Lars George

Publisher: "O'Reilly Media, Inc."

Published: 2011-08-29

Total Pages: 555

ISBN-13: 1449315224

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If you're looking for a scalable storage solution to accommodate a virtually endless amount of data, this book shows you how Apache HBase can fulfill your needs. As the open source implementation of Google's BigTable architecture, HBase scales to billions of rows and millions of columns, while ensuring that write and read performance remain constant. Many IT executives are asking pointed questions about HBase. This book provides meaningful answers, whether you’re evaluating this non-relational database or planning to put it into practice right away. Discover how tight integration with Hadoop makes scalability with HBase easier Distribute large datasets across an inexpensive cluster of commodity servers Access HBase with native Java clients, or with gateway servers providing REST, Avro, or Thrift APIs Get details on HBase’s architecture, including the storage format, write-ahead log, background processes, and more Integrate HBase with Hadoop's MapReduce framework for massively parallelized data processing jobs Learn how to tune clusters, design schemas, copy tables, import bulk data, decommission nodes, and many other tasks

Data Science & Business Analytics
Data Science & Business Analytics

Author: Sneha Kumari

Publisher: Emerald Group Publishing

Published: 2020-12-04

Total Pages: 288

ISBN-13: 1800438761

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Data Science & Business Analytics explores the application of big data and business analytics by academics, researchers, industrial experts, policy makers and practitioners, helping the reader to understand how big data can be efficiently utilized in better managerial applications.

From Big Data to Big Profits
From Big Data to Big Profits

Author: Russell Walker

Publisher: Oxford University Press, USA

Published: 2015

Total Pages: 313

ISBN-13: 0199378320

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In From Big Data to Big Profits, Russell Walker investigates the use of internal Big Data to stimulate innovations for operational effectiveness, and the ways in which external Big Data is developed for gauging, or even prompting, customer buying decisions.

Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence
Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence

Author: Trivedi, Shrawan Kumar

Publisher: IGI Global

Published: 2017-02-14

Total Pages: 465

ISBN-13: 1522520325

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The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.