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Hands-on Big Data

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TypeOfResource
Text
TitleInfo
Title
Hands-on Big Data
Name (authority = orcid); (authorityURI = http://id.loc.gov/vocabulary/identifiers/orcid.html); (type = personal); (valueURI = http://orcid.org/0000-0003-4873-4268)
NamePart (type = family)
Womack
NamePart (type = given)
Ryan
Affiliation
Research & Instructional Services (RIS), Rutgers University
Role
RoleTerm (authority = marcrt); (type = text)
author
Name (authority = RutgersOrg-School); (type = corporate)
NamePart
Rutgers University Libraries
Genre (authority = RULIB-FS)
Conference Paper or Lecture
Note
Presented at IASSIST 41st Annual Conference, "Bridging the Data Divide: Data in the International Context," Minneapolis, Minnesota, June 2, 2015.
OriginInfo
DateCreated (encoding = w3cdtf); (keyDate = yes); (qualifier = exact)
2015
Abstract (type = Abstract)
This workshop is for those of you who, having read about Big Data and seen some of its results in academic studies and the commercial world, would like to get a sense of what actually working with Big Data entails.

The workshop will provide an overview of key technologies for the handling and analysis of large scale datasets, including Hadoop/MapReduce, the RHadoop package, other R packages used for large scale analysis, and Big Data handling environments such as Cloudera, Hortonworks, Tessera, and Amazon Web Services. We will also discuss a few of the primary challenges in successfully completing analysis of large scale data, such as integrating and structuring heterogenous data, handling sparse matrices, and devising effective analytical routines using parallel processing and splitting data. Participants will work with a live demonstration environment that provides a realistic introduction to Big Data Analytics using scripts that will run both on a scaled-down demonstration dataset and on truly large scale data.
Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
PhysicalDescription
InternetMediaType
application/pdf
Extent
52 p.
Subject (authority = local)
Topic
Big Data
Subject (authority = local)
Topic
Hadoop
Subject (authority = local)
Topic
Statistics
RelatedItem (type = host)
TitleInfo
Title
Womack Ryan Collection
Identifier (type = local)
rucore30014400001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3ZW1NPZ
Genre (authority = ExL-Esploro)
Conference paper
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RightsHolder (type = personal)
Name
FamilyName
Womack
GivenName
Ryan
Role
Copyright holder
RightsDeclaration (AUTHORITY = Creative Commons); (ID = https://creativecommons.org/licenses/by-nc-sa/4.0/); (TYPE = Attribution-NonCommercial-ShareAlike (CC BY-NC-SA))
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) 4.0 International License.
RightsDeclaration (AUTHORITY = FS); (ID = rulibRdec0004)
Copyright for scholarly resources published in RUcore is retained by the copyright holder. By virtue of its appearance in this open access medium, you are free to use this resource, with proper attribution, in educational and other non-commercial settings. Other uses, such as reproduction or republication, may require the permission of the copyright holder.
Copyright
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Copyright protected
Availability
Status
Open
Reason
Permission or license
RightsEvent
Type
Permission or license
AssociatedObject
Type
License
Name
Sole author license v. 1
Detail
I hereby grant to Rutgers, The State University of New Jersey (Rutgers) the non-exclusive right to retain, reproduce, and distribute the deposited work (Work) in whole or in part, in and from its electronic format, without fee. This agreement does not represent a transfer of copyright to Rutgers.Rutgers may make and keep more than one copy of the Work for purposes of security, backup, preservation, and access and may migrate the Work to any medium or format for the purpose of preservation and access in the future. Rutgers will not make any alteration, other than as allowed by this agreement, to the Work.I represent and warrant to Rutgers that the Work is my original work. I also represent that the Work does not, to the best of my knowledge, infringe or violate any rights of others.I further represent and warrant that I have obtained all necessary rights to permit Rutgers to reproduce and distribute the Work and that any third-party owned content is clearly identified and acknowledged within the Work.By granting this license, I acknowledge that I have read and agreed to the terms of this agreement and all related RUcore and Rutgers policies.
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RULTechMD (ID = TECHNICAL1)
ContentModel
Document
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