DocumentCode :
169896
Title :
Managing Big Data Effectively - A Cloud Provider and a Cloud Consumer Perspective
Author :
Ludwig, Heiko
Author_Institution :
Almaden Res. Center, IBM Res., San Jose, CA, USA
fYear :
2014
fDate :
1-5 Sept. 2014
Firstpage :
91
Lastpage :
91
Abstract :
Summary form only given. Instrumentation of processes and an organization´s environment provides vast amounts of data that can be used to drivedecisions. Next to setting up data collection, supervising data quality, and applying proper methods of analysis, organizationsface the challenge to set up an infrastructure and architecture to do so efficiently and cost-effectively. Virtualized platformssuch as private or public clouds are the method of choice for deployment, in particular for data analyses not occurringconstantly. A cloud provider, either a commercial Cloud company or an IT organization within an enterprise, will like to set upa cloud platform such that clients can run big data workloads effectively on. Cloud customers would like to set up big dataapplications in a cost-effective and performant way on their platform.This keynote will walk through a few real life big data analysis scenarios from different industries and discuss thechallenges Cloud providers face making trade-offs. Understanding those challenges and solutions help cloud users choose theright match between their algorithm, big data system and cloud platform.
Keywords :
Big Data; business data processing; cloud computing; data analysis; organisational aspects; IT organization; big data analysis scenarios; big data management; cloud consumer perspective; cloud customers; cloud provider; cloud provider perspective; commercial cloud company; data analyses; data collection; data quality; enterprise; private clouds; public clouds; virtualized platforms; Abstracts; Big data; Cloud computing; Conferences; Face; Instruments; Organizations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Enterprise Distributed Object Computing Conference (EDOC), 2014 IEEE 18th International
Conference_Location :
Ulm
ISSN :
1541-7719
Type :
conf
DOI :
10.1109/EDOC.2014.21
Filename :
6972054
Link To Document :
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