BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//HPCwire Japan - ECPv4.9.6//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:HPCwire Japan
X-ORIGINAL-URL:https://www.hpcwire.jp
X-WR-CALDESC:HPCwire Japan のイベント
BEGIN:VTIMEZONE
TZID:"Asia/Tokyo"
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:JST
DTSTART:20130101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20131203
DTEND;VALUE=DATE:20131206
DTSTAMP:20260504T013034
CREATED:20131022T041835Z
LAST-MODIFIED:20131022T041835Z
UID:709-1386028800-1386287999@www.hpcwire.jp
SUMMARY:2nd IEEE International Conference on Big Data Science and Engineering (BDSE2013)
DESCRIPTION:Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture\, manage\, and process the data within a tolerable elapsed time. Such datasets are often from various sources (Variety) yet unstructured such as social media\, sensors\, scientific applications\, surveillance\, video and image archives\, Internet texts and documents\, Internet search indexing\, medical records\, business transactions and web logs; and are of large size (Volume) with fast data in/out (Velocity). More importantly\, big data has to be of high value (Value) and establish trust in it for business decision making (Veracity). Various technologies are being discussed to support the handling of big data such as massively parallel processing databases\, scalable storage systems\, cloud computing platforms\, and MapReduce. Big data is more than simply a matter of size; it is an opportunity to find insights in new and emerging types of data and content\, to make business more agile\, and to answer questions that were previously considered beyond our reach. Distributed systems is a classical research discipline investigating various distributed computing technologies and applications such as cloud computing and MapReduce. With new paradigms and technologies\, distributed systems research keeps going with new innovative outcomes from both industry and academia. For example\, wide deployment of MapReduce is a distributed programming paradigm and an associated implementation to support distributed computing over large big datasets on cloud.  \n
URL:https://www.hpcwire.jp/event/2nd-ieee-international-conference-on-big-data-science-and-engineering-bdse2013
LOCATION:UTS City Campus\, Sydney\, Australia
CATEGORIES:国際会議
END:VEVENT
END:VCALENDAR