Hadoop as Big Data Operating System - The Emerging Approach for Managing Challenges of Enterprise Big Data Platform

被引:6
作者
Mazumdar, Sourav [1 ]
Dhar, Subhankar [2 ]
机构
[1] IBM Software Grp, San Jose, CA USA
[2] San Jose State Univ, San Jose, CA 95192 USA
来源
2015 IEEE FIRST INTERNATIONAL CONFERENCE ON BIG DATA COMPUTING SERVICE AND APPLICATIONS (BIGDATASERVICE 2015) | 2015年
关键词
Business analytics; Big Data; Data Mining; Map Reduce; Hadoop; NoSQL;
D O I
10.1109/BigDataService.2015.72
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Over last few years, innovation in Hadoop and other related Big Data technologies in last few years brings on to the table a lot of promises around better management of enterprise data at much lesser cost and with high value business benefits. In this paper, we propose to delve into details of these challenges from practitioners' perspective based on lessons learnt from various Big Data implementation scenarios. We also aim to discuss the emerging concept of Hadoop as Big Data Operating System to address these challenges with a holistic proposition. Finally, we also plan to provide a prescriptive approach based on best practices which can help moving towards the vision of Enterprise Big Data Platform using Hadoop as Data Operating System balancing between short term objectives and long term goals of managing and maintaining Enterprise Big Data Platform.
引用
收藏
页码:499 / 504
页数:6
相关论文
共 17 条
[1]  
Brewer E.A., 2000, ROBUST DISTRIBUTED S
[2]  
Casado Ruben, 2014, CONCURRENCY COMPUTAT
[3]  
Christian B., 2011, P 25 SEM WEB DAT RES
[4]  
DAS S., 2010, ACM SIGMOD INT C MAN, P987, DOI DOI 10.1145/1807167.1807275
[5]  
DEMCHENKO Y, 2014, INT C COLL TECHN SYS, P104
[6]  
Dhar S., 2014, J INFORM TECHNOLOGY, VXXV
[7]  
Foley M., 2012, HAD SUMM
[8]  
Gantz J., 2012, The Digital Universe in 2020: Big data, Bigger Digital Shadow's, and Biggest Growth in the Far East
[9]  
Ghazal A., 2013, P 2013 ACM SIGMOD IN, P1197, DOI DOI 10.1145/2463676.2463712
[10]  
Harris H., 2014, WHAT IS DATA PRODUCT