Big Data Computing
1st Edition
Published on 5. December 2013
564 pages
978-1-4665-7838-8 (ISBN)
Description
Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Novel approaches and tools have emerged to tackle the challenges of Big Data. Moreover, the technology required for Big Data computing is developing at a satisfactory rate due to market forces and technological evolution. This book presents a mix of theory and industry cases that discuss the technical and practical issues related to Big Data in intelligent information management. It emphasizes the adoption and diffusion of Big Data tools and technologies in real practical applications.
More details
Language
English
Place of publication
Philadelphia, PA
United States
Publishing group
Taylor & Francis Inc
Target group
Professional and scholarly
File size
22,84 MB
ISBN-13
978-1-4665-7838-8 (9781466578388)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Rajendra Akerkar
Big Data Computing
Book
10/2019
1st Edition
Chapman & Hall/CRC
€95.90
Shipment within 15-20 days
Rajendra Akerkar
Big Data Computing
Book
12/2013
1st Edition
CRC Press
€198.50
Shipment within 15-20 days
Content
Introduction: Toward Evolving Knowledge Ecosystems for Big Data Understanding. Tassonomy and Review of Big Data Solutions Navigation. Big Data: Challenges and Opportunities. Semantic Technologies and Big Data: Management of Big Semantic Data. Linked Data in Enterprise Integration. Scalable End-User Access to Big Data. Semantic Data Interoperability: The Key Problem of Big Data. Big Data Processing: Big Data Exploration. Big Data Processing with MapReduce. Efficient Processing of Stream Data over Persistent Data. Big Data and Business: The Economics of Big Data: A Value Perspective on State of the Art and Future Trends. Advanced Data Analytics for Business. Big Data Applications: Big Social Data Analysis. Real-Time Big Data Processing for Domain Experts: An Application to Smart Buildings. Big Data Application: Analyzing Real-Time Electric Meter Data. Scaling of Geographic Space from the Perspective of City and Field Blocks and Using Volunteered Geographic Information. Big Textual Data Analytics and Knowledge Management.
