NDLI: Analytics: Key to Go from Generating Big Data to Deriving Business Value

Content Provider	IEEE Xplore Digital Library
Author	Arora, D. Malik, P.
Copyright Year	2015
Description	Author affiliation: Bus. Analytics & Strategy, IBM Global Bus. Services, San Jose, CA, USA (Malik, P.) \|\| Dept. of Electr. & Comput. Eng., Univ. of Victoria, Victoria, TX, USA (Arora, D.)
Abstract	The potential to extract actionable insights from Big Data has gained increased attention of researchers in academia as well as several industrial sectors. The field has become interesting and problems look even more exciting to solve ever since organizations have been trying to tame large volumes of complex and fast arriving Big Data streams through newer computing paradigms. However, extracting meaningful and actionable information from Big Data is a challenging and daunting task. The ability to generate value from large volumes of data is an art which combined with analytical skills needs to be mastered in order to gain competitive advantage in business. The ability of organizations to leverage the emerging technologies and integrate Big Data into their enterprise architectures effectively depends on the maturity level of the technology and business teams, capabilities they develop as well as the strategies they adopt. In this paper, through selected use cases, we demonstrate how statistical analyses, machine learning algorithms, optimization and text mining algorithms can be applied to extract meaningful insights from the data available through social media, online commerce, telecommunication industry, smart utility meters and used for variety of business benefits, including improving security. The nature of applied analytical techniques largely depends on the underlying nature of the problem so a one-size-fits-all solution hardly exists. Deriving information from Big Data is also subject to challenges associated with data security and privacy. These and other challenges are discussed in context of the selected problems to illustrate the potential of Big Data analytics.
Starting Page	446
Ending Page	452
File Size	573442
Page Count	7
File Format	PDF
ISBN	9781479981281
DOI	10.1109/BigDataService.2015.62
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-03-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Sentiment analysis Machine learning algorithms Algorithms Companies Machine learning Big data Review Security
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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