synopsis on big data analytics pdf

/CS1 78 0 R /T1_3 38 0 R 20 0 obj [ (in the ar) -15 (ticle\056) 35 ( ) ] TJ 1 0 0 1 72 769.89 cm (RESEARCH) Tj Big Data analytics and the Apache Hadoop open source project are rapidly emerging as the preferred solution to address business and technology trends that are disrupting traditional data management and processing. /MediaBox [ 0 0 595.276 841.89 ] /T1_5 1 Tf << [ (A) -10 (par) -15 (t fr) 10 (om mark) 15 (et intellig) 15 (ence\054) 35 ( it is being applied in div) 10 (er) 10 (se ar) 10 (eas suc) -10 (h ) ] TJ /BleedBox [ 0 0 595.276 841.89 ] /ExtGState << /T1_0 42 0 R /T1_5 1 Tf The model introduces a framework for converting data to actionable knowledge and mitigating potential risk to the [ (Mor) 15 (g) 15 (an\054) 35 ( S\056L\056\054) 35 ( \046 Har) 20 (ding) -30 (\054) 35 ( D) 30 (\056J\056) 35 ( \0502006\051\056) 35 ( Matc) -10 (hing Estimator) 10 (s of Causal E) 46 (f) 10 (f) 15 (ects\072) 35 ( ) ] TJ EMC /T1_5 13 0 R /ProcSet [ /ImageC /ImageB /Text /PDF /ImageI ] /GS1 gs /ca 1 /T1_4 13 0 R /Type /ExtGState ( ) Tj (Nadir Zanini ) Tj endobj /FontDescriptor 15 0 R 244.42 52.02 Td >> /T1_1 1 Tf T* 2 Analytics: The real-world use of big data in financial services At the same time, these firms are dealing with a very diverse and demanding customer base that insists on communicating and transacting business in new and varied ways, any time of the … /SA true T* /GS0 12 0 R /T1_4 1 Tf /CropBox [ 0 0 595.276 841.89 ] [ (Gill\054) 35 ( ) 70 (T) 30 (\056) 35 ( \0502013\051\056) 35 ( Earl) 10 (y entry GCSE candidates\072) 35 ( Do the) 10 (y perf) 15 (orm to their potential\077 ) ] TJ (et al) Tj endobj /Parent 1 0 R >> /ProcSet [ /PDF /Text ] 0 0 0 1 k >> T* >> /Span << Big Data, Analytics & Artificial Intelligence | 4 Today’s health care system, in the United States and throughout the world, is still entering the 21st century. <> endobj [ (ISSUE ) -28 (18 ) ] TJ T* /Encoding 14 0 R [ (small\054) 35 ( ar) 10 (e implementing \050or planning to implement\051 big data 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848 ] /T1_6 1 Tf 8 0 obj endobj stream [ (fr) 10 (om the \037r) 10 (st sitting of a GCSE will count in perf) 15 (ormance tables\056) 35 ( ) 70 (T) 15 (his is ) ] TJ 14 0 obj 0 G /Contents 10 0 R Q [ (with boosted r) 10 (egr) 10 (ession f) 15 (or e) 10 (v) 25 (aluating causal ef) 10 (f) 15 (ects in observ) 25 (ational studies\056) 35 ( ) ] TJ ( ) Tj [ (f) 15 (or lar) 15 (g) 15 (e databases r) 10 (equir) 10 (ing comple) 10 (x pr) 10 (ocessing and visualisation w) 10 (hic) -10 (h ) ] TJ 0.1 Tc We then move on to give some examples of the application area of big data analytics. >> Enterprises can gain a competitive advantage by being early adopters of big data analytics. /Type /Page <> /T1_5 25 0 R /Filter /FlateDecode 1.134 -1.467 Td -0.01 Tc << 0 -1.576 TD ( ) Tj [ (10\054) 35 ( but c) -10 (hang) 15 (es to accountability measur) 10 (es mean that onl) 10 (y the r) 10 (esult ) ] TJ That’s not to say that SIEM vendors will provide big data distributions as part of their solution, rather most will architect big data techniques into their platforms to … 0.275 0.095 0 0 K (16) Tj W 1.031 -1.576 Td /T1_5 1 Tf 0 G /T1_5 1 Tf [ (adaptiv) 10 (e testing w) 10 (hic) -10 (h will pr) 10 (o) 15 (vide ne) 10 (w str) 10 (eams of data w) 10 (hic) -10 (h could be ) ] TJ /T1_4 1 Tf >> Our research indicates that China is aggressively working toward becoming a global leader in big data analytics. /T1_2 1 Tf But it’s of no value unless you know how to put your big data … 4 0 obj T* 1 0 0 0 k Organizations are capturing, storing, and analyzing data that has high volume, 0 0 0 1 k /Span << 2 0 obj [ <0035004800560048004400550046004b> -277 <0030004400570057004800550056001d> -371 <0024> -277 <00260044005000450055004c0047004a0048> -278 <0024005600560048005600560050004800510057> -278 <005300580045004f004c004600440057004c00520051> ] TJ >> ( ) Tj endobj 2 0 obj /Type /ExtGState /ActualText (��\000\011) /ActualText (ers) [ (to the dif) 10 (f) 15 (er) 10 (ent type of str) 10 (uctur) 10 (ed or unstr) 10 (uctur) 10 (ed data suc) -10 (h as te) 10 (xt and ) ] TJ /Contents 58 0 R endobj /GS0 12 0 R endobj q endobj Last updated on Sep 21, 2020. /T1_5 1 Tf 0 -1.467 TD [ (industr) 10 (ies suc) -10 (h as a) 10 (viation and hea) 10 (v) 5 (y mac) -10 (hinery) 45 (\054) 35 ( impr) 10 (o) 15 (ving public ) ] TJ Big Data & Analytics EXPECTATIVAS: DIFERENTESTIPOS DE USUARIOS Asegurar la velocidadde los análisisde datos Administrar el caos Implementar desarrollosen forma fluida Asegurar la gobernabilidad de la información Realizar nuevosy más rápidos análisispara mejorar los negocios Tomardecisionesde negocios [ (to this\054) 35 ( w) 10 (e discuss ne) 10 (w f) 15 (orms of assessment suc) -10 (h as e\055assessment and ) ] TJ (22) Tj <> << Q /T1_5 1 Tf (Big data) Tj 0 -1.576 TD /T1_2 34 0 R 1.031 -1.576 Td /T1_5 30 0 R <> [ (\050BBC) -50 (\054) 35 ( 2013\073) 35 ( Lohr) 30 (\054) 35 ( 2012\051\056) 35 ( ) ] TJ [ (test r) 10 (ecor) 20 (ds\054) 35 ( beha) 10 (viour patterns\054) 35 ( and teac) -10 (her observ) 25 (ations o) 15 (v) 10 (er a per) 10 (iod ) ] TJ /Type /Encoding >> /MC0 << T* 4 Smarter Infrastructure: Thoughts on big data and analytics Big data and the use of analytics on that data We begin by discussing what big data is and the use of analytics on that data. /F1 7.97 Tf endobj endobj /Span << 1 0 0 1 0 0 cm ( ) Tj /TrimBox [ 0 0 595.276 841.89 ] it is not all firms, just those recruiting big data sta. /Font << ET /Im2 84 0 R <> >> endstream /Parent 1 0 R [ (implementation of pr) 10 (opensity scor) 10 (e matc) -10 (hing) -30 (\056) 35 ( ) ] TJ /Type /Page Introduction to Data Science: A Beginner's Guide. � �Fn8�BG}��>�:1��Z 1.134 -1.467 Td /T1_5 1 Tf 0.1 Tc 9 0 obj /GS0 12 0 R 0 G [ (\0501\051\054) 35 ( 31\22672\056) ] TJ 0 Tc /T1_6 30 0 R [ ( ) -28 (SUMMER ) -28 (2014) ] TJ Well-managed, trusted data leads to trusted analytics and trusted decisions. /ExtGState << [ (\0504\051\054) 35 ( 403\226425\056) ] TJ 1.619 0 Td n [ 11 0 R] [ (or high v) 25 (ar) 10 (iety inf) 15 (ormation assets that r) 10 (equir) 10 (e ne) 10 (w f) 15 (orms of pr) 10 (ocessing ) ] TJ 8.468 0 Td /F1 7.97 Tf 0 -1.576 TD [ (tr) 20 (a) 10 (v) 10 (elling) -30 (\054) 35 ( banking) -30 (\054) 35 ( man) 10 (uf) 10 (actur) 10 (ing and tr) 20 (ading) -30 (\054) 35 ( public utilities\054) 35 ( state ) ] TJ >> BDC >> ET /ArtBox [ 0 0 595.276 841.89 ] endobj [ (J) 5 (our) -10 (nal of Economic S) 26 (ur) -35 (v) 15 (e) -10 (ys\054) ] TJ >> /FontFamily (Bliss) /CA 1 04 Oracle Big Data 모델별세부사항 X6-2 Full Rack Starter Rack Elastic Configuration Compute/Storage Nodes 18 6 1 Cores 792 264 44 Memory(GB) 4,608(4.5TB) 1,536(1.5TB) 256 Raw Storage Capacity(TB) 1,728 576 96 InfiniBand Leaf Switch 2 2 InfiniBand Spine Switch 1 1 Starter Rack의 switch 사용 Ethernet Switch 1 1 0 Tc 13 9 0 0 9 42.5197 441.9187 Tm Q /T1_2 1 Tf /F2 18 0 R -0.01 Tc �W�z��,5{U/�RyUUf�O�ʌ�m��d��� �_��geʬ�rS�ɼ�ͪ�1t+���U��m+m\뽴i�B��_��{�ު��€V���6�lJ��ҕ����L�50G,ߛ`i� }bG��ߺ�u��\��qϿ��O��ׁx �W_����i�GU��4�d�v&Y�*yJ���:��t� � T* I�t��T�"}NQ���zG��u�z����3s�2�J�"�-;&�~+��99�:�t��2�e�˿]'����=�M�^�g ���-�-ͭ�]������0��z� -0.03 Tc 1 0 obj /ArtBox [ 0 0 595.276 841.89 ] /FirstChar 30 on a) what big data is, b) how it can improve security analytics, and c) how it will — or won’t — integrate with SIEM. << /BleedBox [ 0 0 595.276 841.89 ] New Software and Hardware tools are emerging and disruptive. /T1_5 1 Tf >> /T1_5 30 0 R (9) Tj 14 0 obj endobj Introduction Organizations are able to access more data today than ever before. 0 g T* <> T* /TrimBox [ 0 0 595.276 841.89 ] -1.134 -2 Td 0 G [ (Psyc) 10 (holo) 10 (gical M) 21 (ethods\054) ] TJ 0 Tc Further research could also estimate the average treatment effect for the treated in … EBA REPORT ON BIG DATA AND ADVANCED ANALYTICS 6 project, in a sort of Zethical by design [ approach that can influence considerations about governance structures. ET /Rotate 0 endobj /ExtGState << /Resources << >> [ (softw) 25 (ar) 10 (e tools to captur) 10 (e\054) 35 ( stor) 10 (e\054) 35 ( manag) 15 (e\054) 35 ( and anal) 10 (yz) 5 (e\224) 45 ( \050Man) 15 (yika ) ] TJ /Differences [ 30 /fl /fi ] 13 0 0 13 42.5197 397.9869 Tm 0.4 0.4 0.4 RG /T1_4 13 0 R Furthermore, its boundary with Artificial Intelligence becomes blurring. /GS1 11 0 R -1.134 -2 Td /T1_4 25 0 R >> BDC Click Download or Read Online Button to get Access Creating Value with Big Data Analytics ebook. /CS0 80 0 R [ (R) 24 (esear) 20 (c) -10 (h Division) ] TJ /Im1 85 0 R endobj /Im0 85 0 R /CropBox [ 0 0 595.276 841.89 ] /ActualText (a) [ (observ) 25 (ational studies f) 15 (or causal ef) 10 (f) 15 (ects\056) 35 ( ) ] TJ 0 -1.576 TD T* 1.031 -1.576 Td /T1_1 1 Tf The Big Data Analytics area evolves in a speed that was seldom seen in the history. endobj <> (M) Tj /TT0 71 0 R 0 Tc -1.031 -1.576 Td [ (tr) 20 (aining cour) 10 (ses in big data of) 10 (f) 15 (er) 10 (ed b) 15 (y v) 25 (ar) 10 (ious univ) 10 (er) 10 (sities ar) 10 (e mentioned ) ] TJ [ (McCaf) 10 (fr) 10 (e) 10 (y) 45 (\054) 35 ( D) 30 (\056F) 60 (\056\054) 35 ( Ridg) 15 (e) 10 (w) 25 (a) 15 (y) 45 (\054) 35 ( G\056\054) 35 ( \046 Morr) 20 (al\054) 35 ( ) 70 (A\056R\056) 35 ( \0502004\051\056) 35 ( Pr) 10 (opensity scor) 10 (e estimation ) ] TJ Costs remain high, there are great inefficiencies, and, for a large percentage of the population globally, access to care endobj 0.1 Tc /AIS false Q n /ItalicAngle 0 /SMask /None [ (applications in v) 25 (ar) 10 (ious \037elds\054) 35 ( including education\056) 35 ( ) 85 (W) 45 (e also descr) 10 (ibe the ) ] TJ 0 -1.576 TD 0.55 0.19 0 0 k 6.5 0 0 6.5 42.5197 659.0757 Tm 7 0 obj The need to analyze and leverage trend data collected by businesses is one of the main drivers for Big Data analysis tools. <> 8.25 0 0 8.25 42.5197 793.0757 Tm /Subtype /Type1 /T1_2 1 Tf This collected data has variety of nature, some might be structured [ (ar) 10 (eas of r) 10 (esear) 20 (c) -10 (h \050Eina) 10 (v \046 Le) 10 (vin\054) 35 ( 2013\073) 35 ( Ma) 15 (y) 10 (er) 30 (\055Sc) -10 (h�nber) 15 (g) 15 (er \046 Cukier) 30 (\054) 35 ( ) ] TJ Big Data Analytics Overall Goals of Big Data Analytics in Healthcare Genomic Behavioral Public Health. /T1_0 42 0 R /TT1 68 0 R /T1_0 1 Tf ( ) Tj /T1_3 42 0 R The people who work on big data analytics are called data scientist these days and we explain what it encompasses. <> /MediaBox [ 0 0 595.276 841.89 ] /Span << EMC [ (and using the r) 10 (esults so obtained\056) 35 ( Speci\037call) 10 (y) 45 (\054) 35 ( big data is a term used ) ] TJ /GS1 11 0 R /Length 4833 >> <>/ExtGState<>/XObject<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/MediaBox[ 0 0 612 792] /Contents 4 0 R/Group<>/Tabs/S/StructParents 0>> T* Volume 34 Article 65 Tutorial: Big Data Analytics: Concepts, Technologies, and Applications Hugh J. Watson Department of MIS, University of Georgia hwatson@uga.edu We have entered the big data era. [ (lik) 15 (el) 10 (y to lead to a f) 10 (all in earl) 10 (y entry because sc) -10 (hools ma) 15 (y w) 25 (ant to w) 25 (ait ) ] TJ 12 0 obj /TrimBox [ 0 0 595.276 841.89 ] T* /op false Top big data analytics use cases Big data can benefit every industry and every organization. 8 0 obj Q Audience. >> 5.346 0 Td /T1_3 42 0 R << /F1 50 0 R Big data analytics refers to the strategy of analyzing large volumes of data, or big data. 7.5 0 0 7.5 42.5197 635.076 Tm [ (Sociolo) 10 (gical M) 21 (ethods \046 R) 41 (esear) 15 (c) 10 (h\054) 20 ( ) ] TJ q /Resources << Die wichtigsten davon sind: Die Datenbeschaffung aus verschiedenen Quellen mithilfe von Suchabfragen, die Optimierung und Auswertung der gewonnenen Daten sowie; die Analyse der Daten und Präsentation der Ergebnisse. /Font << /CapHeight 659 [ (\050W) 15 (ikipedia\054) 35 ( 2014a\051\056) 35 ( ) 70 (A) 33 (ccor) 20 (ding to the McKinse) 10 (y Global Institute\054) 35 ( ) 70 (\223Big data ) ] TJ We may no longer find a clear distinction on what is a Big Data Analytics problem and what is an AI problem. /T1_4 13 0 R We start with defining the term big data and explaining why it matters. /Length 14583 • – – – ata analytics is necessarily a Big d joint effort by researchers from academic institutions, government and society and industry. [ (\221Big data\222) 45 ( is f) 10 (ast becoming an ar) 10 (ea of gr) 10 (eat impor) -15 (tance f) 15 (or businesses ) ] TJ [ (V) 20 (ikas Dha) 20 (w) 25 (an ) ] TJ T* 0 -1.576 TD << /GS0 gs (\057) Tj /Rotate 0 /Parent 1 0 R /Type /Page /StemV 120 /AIS false 10 0 obj -1.134 -2 Td >> Hence, big data analytics is really about two things—big data and analytics—plus how the two have teamed up to [ (F) 20 (inall) 10 (y) 45 (\054) 35 ( it will be inter) 10 (esting to see the impact of GCSE r) 10 (ef) 15 (orms on ) ] TJ 3 0 obj /T1_2 34 0 R 15 0 obj <> 0 0 595.276 841.89 re T* /LastChar 181 /BaseEncoding /WinAnsiEncoding Discover the top twenty-two use cases for big data. << 0 -1.576 TD [ (of time f) 15 (or pr) 10 (o) 15 (viding mor) 10 (e accur) 20 (ate and timel) 10 (y interv) 10 (entions\056) 35 ( In addition ) ] TJ /T1_2 1 Tf [ (Intr) 10 (oduction) ] TJ /T1_2 1 Tf [ (In this ar) -15 (ticle w) 10 (e g) 15 (iv) 10 (e an intr) 10 (oduction to big data and some of its ) ] TJ >> BDC 0 0 0 0 k [ (Biometr) -10 (ika\054) ] TJ [ (ef) 10 (f) 15 (ect f) 15 (or the tr) 10 (eated in the case of tw) 10 (o tr) 10 (eatment gr) 10 (oups\054) 35 ( to see if taking) -10 ( ) ] TJ /Annots [ 57 0 R ] 0 g >> [ (\0501\051\054) 35 ( 41\22655\056) ] TJ 0.1 Tc /GS1 11 0 R /BleedBox [ 0 0 595.276 841.89 ] /Font << [ (R) 41 (ef) 12 (er) 13 (ences) ] TJ /T1_0 42 0 R [ (g) 15 (etting them to sit GCSEs earl) 10 (y and then r) 10 (e\055sit if the) 10 (y under) 20 (perf) 15 (orm\056) 35 ( ) ] TJ /ProcSet [ /PDF /Text ] [ (A) -10 (pplications in the education industry mentioned in this ar) -15 (ticle include ) ] TJ 0 -1.576 TD /T1_2 1 Tf >> /ProcSet [ /PDF /Text /ImageC /ImageI ] << Introduction to Big Data Analytics Big data analytics is where advanced analytic techniques operate on big data sets. /Contents 89 0 R 15 0 obj 0 Tc endobj 0 -1.467 TD 0 -1.576 TD 6 0 obj /T1_5 1 Tf [ (tw) 10 (o or mor) 10 (e GCSEs earl) 10 (y is bene\037cial to these students or not\056) ] TJ [ (GCSEs earl) 10 (y) 45 (\056) 35 ( F) 49 (ur) -15 (ther r) 10 (esear) 20 (c) -10 (h could also estimate the a) 10 (v) 10 (er) 20 (ag) 15 (e tr) 10 (eatment) -10 ( ) ] TJ /T1_4 25 0 R /T1_2 34 0 R 3 0 obj >> 0 -1.576 TD 0.4 0.4 0.4 rg /ActualText (��\000\011) q endobj 0 -1.576 TD /Type /Catalog /T1_0 1 Tf <> /Font << 0 0 0 1 k /BleedBox [ 0 0 595.276 841.89 ] [ (use of big data f) 15 (or the monitor) 10 (ing of social media \050f) 15 (or instance Link) 15 (edIn\054) 35 ( ) ] TJ /T1_5 30 0 R [ (impact\056) 35 ( Manc) -10 (hester\072) 35 ( Ofsted\056) ] TJ W [ (r) 10 (ef) 15 (er) 10 (s to datasets w) 10 (hose siz) 5 (e is be) 10 (y) 10 (ond the ability of typical database ) ] TJ Ebook. PDF - Open Access | Big Data Analytics and Its Applications /T1_3 1 Tf stream q 96.56 0 Td /T1_5 30 0 R R��(�yyN����n];����^��+ _��L�_T눑�xt�~W�>ioW>@Xϡ��ǿ���L������9_�чs��x��]�(%�R{���9�{�$� 7~��5��,��J��4��6G��,S��n�ؾ�_��H\�������p����@� /TrimBox [ 0 0 595.276 841.89 ] [ (R) 41 (esear) 15 (c) 10 (h Matter) -15 (s\072) 25 ( ) 30 (A Cambr) -10 (idge ) 30 (Assessmen) 5 (t Publication\054) ] TJ [ <008b> -278 <00380026002f00280036> -278 <0015001300140017> ] TJ ( ) Tj q <> 12 0 obj 1.134 -1.467 Td /T1_3 38 0 R /T1_1 38 0 R 16 0 obj >> >> /Subtype /Type1C vernment and industry are The go sources of Big Data, and providers of problems and challenges, /GS0 gs 5) Make intelligent, data-driven decisions. << 10 0 obj Amazon Web Services – Big Data Analytics Options on AWS Page 6 of 56 handle. /T1_2 1 Tf 1.134 -1.467 Td /GS0 gs Zunächst stellt sich bei der Big Data Analytics die Aufgabe, riesige Datenmengen unterschiedlichen … 0.378 0 Td /Ascent 848 /F1 7.97 Tf [ (n) 10 (o) 10 (t) 10 ( ) 10 (e) 10 (n) 10 (t) 10 (e) 10 (r) 10 ( ) 10 (e) 10 (a) 10 (r) 10 (l) 20 (y) 10 ( ) 10 (w) 20 (o) 10 (u) 10 (l) 10 (d) 10 ( ) 10 (h) 10 (a) 20 (v) 20 (e) 10 ( ) 10 (p) 10 (e) 10 (r) 10 (f) 25 (o) 10 (r) 10 (m) 10 (e) 10 (d) 10 ( ) 10 (w) 20 (o) 10 (r) 20 (s) 10 (e) 10 ( ) 10 (i) 10 (f) 10 ( ) 10 (t) 10 (h) 10 (e) 20 (y) 10 ( ) 10 (h) 10 (a) 10 (d) 10 ( ) 10 (t) 10 (a) 10 (k) 25 (e) 10 (n) 10 ( ) 10 (t) 10 (w) 20 (o) 10 ( ) 10 (o) 10 (r) 10 ( ) 10 (m) 10 (o) 10 (r) 20 (e ) ] TJ [ <004b005700570053001d00120012005a005a005a001100460044005000450055004c0047004a00480044005600560048005600560050004800510057001100520055004a00110058004e00120055004800560048004400550046004b0010> -62 <00500044005700570048005500560012> ] TJ /CropBox [ 0 0 595.276 841.89 ] [ (optimization\224) 45 ( \050Be) 10 (y) 10 (er \046 Lane) 10 (y) 45 (\054) 35 ( 2012\051\056) 35 ( ) 70 (T) 15 (he term ) 70 (\221v) 10 (olume\222) 45 ( her) 10 (e indicates ) ] TJ /Producer (PyPDF2) /Type /Pages ET /T1_2 1 Tf 0 g /T1_3 38 0 R /OPM 1 >> endobj ��?�,����!8[���p,�` ��8�UC%�� }!�G=F���X�����H���)���:��,�]rЉ ��K'�;�f�&�K��u�@F��&��Z1-�ac�.�h\�Vk. >> ( ) Tj >> /F2 7.97 Tf 0 -1.576 TD >> 0 -1.576 TD 0 -1.576 TD q T* [ (T) 75 (ec) -10 (hnolo) 10 (g) 15 (ical adv) 25 (ances in r) 10 (ecent y) 10 (ear) 10 (s ha) 10 (v) 10 (e led to a signi\037cant amount ) ] TJ (36) Tj >> 1 0 0 1 42.5197 505.0053 cm >> /T1_2 1 Tf tdwi.org 5 Introduction 1 See the TDWI Best Practices Report Next Generation Data Warehouse Platforms (Q4 2009), available on tdwi.org. 11 0 obj x���Ko�@����hW�zf��EB�$i*EJ��q( ����]�V��%p`wG�|�؝!�7��t�~>�l&�o�3��Z�w��|9��W�����Ƌ>V��j]�p1��8B���#㾋ú���`G�8ʯa�G�zRh �*3�N�����gf��nO�q��@��Oqt�}���X���C���w;�:� y�i�BHЖ��(zP�4���������Q K�j��҉ 0 -1.576 TD endobj BT 8.25 0 0 8.25 42.5197 375.9869 Tm 0 Tc << 0.55 0.19 0 0 k Since the dawn of the computer age, people have speculated about how humans would harness technology in the future. -1.031 -1.576 Td /GS1 gs Big data analytics refers to the application of advanced data analysis techniques to datasets that are very large, diverse (including structured and unstructured data), and often arriving in real time. EMC >> /Descent -236 /BM /Normal EMC >> /Kids [ 3 0 R 4 0 R 5 0 R 6 0 R 7 0 R 8 0 R ] /Metadata 77 0 R /T1_2 1 Tf BT /C0_0 59 0 R EMC T* Summary: This chapter gives an overview of the field big data analytics. [ (\0501\051\054) 35 ( 3\22660\056) ] TJ /T1_2 34 0 R /ExtGState << T* >> << /T1_1 46 0 R [ (and g) 15 (o) 15 (v) 10 (ernance\054) 35 ( spor) -15 (ts\054) 35 ( enter) -15 (tainment\054) 35 ( science\054) 35 ( education and health\056) 35 ( ) ] TJ /XHeight 473 << Big Data analytics – the process of analyzing and mining Big Data – can produce operational and business knowledge at an unprecedented scale and specificity. T* /T1_1 1 Tf 17 0 obj >> BDC 0 -1.576 TD [ (combination of data fr) 10 (om v) 25 (ar) 10 (ious sour) 20 (ces and under) 10 (standing patterns ) ] TJ /ArtBox [ 0 0 595.276 841.89 ] 9 0 obj PDF Version Quick Guide Resources Job Search Discussion. T* 0.4 0.4 0.4 RG 0 -2.223 TD /Resources << /T1_0 46 0 R ET /Properties << endstream ( ) Tj /MediaBox [ 0 0 595.276 841.89 ] /ProcSet [ /PDF /Text ] /OP false /FontName /XSWKMI+Bliss-Bold endobj /C0_0 59 0 R /Type /FontDescriptor /Widths [ 619 601 238 0 0 0 0 894 0 0 347 347 0 0 231 363 231 394 542 542 542 542 542 542 542 542 542 542 231 0 556 592 0 0 0 626 539 608 668 475 467 681 695 255 331 578 432 797 729 745 502 745 563 501 539 684 0 949 0 586 0 0 0 0 0 0 0 494 528 446 530 496 347 504 536 260 270 485 270 832 539 544 529 534 363 418 385 534 487 751 490 523 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 235 410 424 0 500 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 542 ] <> [ (cannot be ef\037cientl) 10 (y handled b) 15 (y tr) 20 (aditional data pr) 10 (ocessing softw) 25 (ar) 10 (e ) ] TJ endobj /OPM 1 (and ) Tj Increasingly, big data feeds today’s advanced analytics endeavors such as artificial intelligence. 8.25 0 0 8.25 311.811 375.9869 Tm /GS0 gs /T1_3 42 0 R /ToUnicode 17 0 R /T1_2 1 Tf /Resources << 6 0 obj (Big data and social media analytics) Tj 1 0 obj endobj 0 -1.576 TD Ten years ago, “big data analytics” was one of 0.216 0.773 0.969 RG 0 -1.576 TD /T1_2 34 0 R %PDF-1.3 /GS1 11 0 R 0 Tc By contrast, on AWS you can provision more capacity and compute in a matter of minutes, meaning that your big data applications grow and shrink as demand dictates, and your system runs as close to optimal efficiency as possible. << /MediaBox [ 0 0 595.276 841.89 ] /ArtBox [ 0 0 595.276 841.89 ] <> [ (of data w) 10 (hic) -10 (h is no) 15 (w g) 15 (ener) 20 (ated in e) 10 (v) 10 (eryda) 15 (y lif) 15 (e\054) 35 ( suc) -10 (h as shopping) -30 (\054) 35 ( ) ] TJ /MediaBox [ 0 0 595.276 841.89 ] This tutorial has been prepared for software professionals aspiring to learn the basics of Big Data Analytics. /ca 1 (ERS) Tj [ (until students ar) 10 (e r) 10 (ead) 10 (y to ac) -10 (hie) 10 (v) 10 (e their best possible gr) 20 (ade\054) 35 ( r) 20 (ather than ) ] TJ 1.134 -1.467 Td -0.01 Tc /T1_1 46 0 R (35) Tj /BleedBox [ 0 0 595.276 841.89 ] T* >> BDC /T1_2 1 Tf Either way, big data analytics is how companies gain value and insights from data. /T1_1 1 Tf endobj %PDF-1.7 [ (monitor) 10 (ing and e) 10 (v) 25 (aluation of tests\056) ] TJ 1.134 -1.467 Td [ (the amount of earl) 10 (y entry) 45 (\056) 35 ( Students will still be able to sit GCSEs in ) 85 (Y) 95 (ear ) ] TJ Explainability and interpretability: a model is explainable when its internal behaviour can be directly understood by humans (interpretability) or when explanations (justifications) can be /CA 1 1.031 -1.576 Td Big Data has been used for advanced analytics in many domains but hardly, if … endobj /T1_2 1 Tf << Big Data Analytics Tutorial in PDF - You can download the PDF of this wonderful tutorial by paying a nominal price of $9.99. -1.134 -2 Td 2016 BIG DATA THE WHATS, WHYS, AND HOWS OF DATA ANALYTICS BIG DATA ANALYTICS IS MAINSTREAM. 0 -1.576 TD /GS1 11 0 R (TT) Tj (\174) Tj /Parent 1 0 R T* [ (the stud) 10 (y of big data has g) 15 (ained pr) 10 (ominence among sc) -10 (holar) 10 (s in dif) 10 (f) 15 (er) 10 (ent ) ] TJ 0 0 m /ColorSpace << << Purpose – The purpose of this paper is to provide a conceptual model for the transformation of big data sets into actionable knowledge. <> big data analytics follow for storage, analysis and maintenance [6] enumerated some of the basic procedures generally big data analytics follow. /ExtGState << >> /SA true /Contents 66 0 R endobj /GS1 gs 4.855 0 Td /T1_1 38 0 R stream 0 -1.576 TD ˔���J� �Me� �>�-O�����+O:��S^\~��@��K(����*ȿ��4�(��j���z��߽+�7�1��n����. /GS0 12 0 R /TrimBox [ 0 0 595.276 841.89 ] ET /FontStretch /Normal /Type /Page /ActualText (��\000\011) /Rotate 0 /F1 7.97 Tf 0 0 595.276 841.89 re >> /CropBox [ 0 0 595.276 841.89 ] /Contents 88 0 R /T1_1 46 0 R S 8.5 0 0 8.5 42.5197 502.2573 Tm /ActualText (�� \010) -1.031 -1.576 Td 21 0 0 21 42.5197 467.2573 Tm [ (C) 37 (ommer) 20 (cial or) 15 (g) 15 (anisations\054) 35 ( r) 10 (esear) 20 (c) -10 (h bodies and g) 15 (o) 15 (v) 10 (ernments ha) 10 (v) 10 (e star) -15 (ted ) ] TJ /T1_2 34 0 R /T1_0 46 0 R 9 Purpose of this Tutorial Two-fold objectives: Introduce the data mining researchers to the sources available and the possible challenges and techniques associated with using big data in healthcare domain. /Type /Page /T1_6 13 0 R 13 0 obj [ (the combination of v) 25 (ar) 10 (ious sour) 20 (ces of inf) 15 (ormation about pupils suc) -10 (h as ) ] TJ /Span << [ (Pr) 10 (ospects and Pitf) 10 (alls in ) 70 (T) 15 (heory and Pr) 20 (actice\056) 35 ( ) ] TJ [ (\054) 35 ( 23\22640\056) ] TJ /ArtBox [ 0 0 595.276 841.89 ] Creating Value with Big Data Analytics by Verhoef, Peter (Paperback) Download Creating Value with Big Data Analytics or Read Creating Value with Big Data Analytics online books in PDF, EPUB and Mobi Format. /CropBox [ 0 0 595.276 841.89 ] H�lT{Tw�!��d��PI`�����R��ED-�""� �j+Z��[Ԫ��(��j��@]_���׺*�E�(w�7�� ��O��Ι?�|�{����wIB�D�$��33qZ��?h���� �٘�T��_:W�Hkl�/�m��7����� W8@�jF����L��2M�t͢�5�:�n��Y���TK�&�l�Ddf�j&�r f�F���΢�4[r̖�<1��05 �L}^�&A���,ӥ)�&�!g _�ԟ�� �B;�0�b'"� �D�(��QF��HrG��B�"��i��z�K/� Big Data Analytics Notes Pdf Download & List of Reference Books … [ (tapped f) 15 (or stud) 10 (ying the perf) 15 (ormance of test tak) 15 (er) 10 (s in mor) 10 (e detail and f) 15 (or ) ] TJ /T1_6 25 0 R >> /Span << /Rotate 0 Big Data Analytics: Adoption and Employment Trends, 20122017 of big data recruiters say it is di cult to find people with the required skills and experience, ie. /TrimBox [ 0 0 595.276 841.89 ] /GS0 12 0 R /GS2 87 0 R 7 0 0 7 42.5197 27.6981 Tm Our bloggers have written several posts on this topic and how the use of data and analytics on those data is [ <0011> ] TJ /T1_2 1 Tf q [ (utilities and tr) 20 (af\037c manag) 15 (ement\054) 35 ( oil and g) 15 (as e) 10 (xplor) 20 (ation\054) 35 ( telecoms\054) 35 ( r) 10 (etail\054) 35 ( ) ] TJ /T1_5 1 Tf /ProcSet [ /PDF /Text ] [ (2013\051 as w) 10 (ell as g) 15 (ener) 20 (ating inter) 10 (est fr) 10 (om the non\055academic w) 10 (orld ) ] TJ T* /Type /Font -57.83 52.02 Td 0 G /Type /Page 0 g ( ) Tj [ (combination of the data collected fr) 10 (om v) 25 (ar) 10 (ious sour) 20 (ces\054) 35 ( pr) 10 (ocessing it ) ] TJ 14 w 7 0 0 7 62.3666 27.6981 Tm 19 0 obj /FontWeight 700 [ (T) 15 (he concept of big data encompasses the collection of data\054) 35 ( the ) ] TJ [ (Ofsted \0502013\051\056) 35 ( Sc) -10 (hools\222) 45 ( use of earl) 10 (y entry to GCSE e) 10 (xaminations\056) 35 ( Its usag) 15 (e and ) ] TJ >> [ (mark) 15 (et intellig) 15 (ence and educational r) 10 (esear) 20 (c) -10 (h\056) 35 ( Businesses\054) 35 ( lar) 15 (g) 15 (e and ) ] TJ /Count 6 BT /T1_0 1 Tf Big data and social media analytics Vikas Dhawan and Nadir Zanini Research Division not enter early would have performed worse if they had taken two or more GCSEs early. 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T* n Why Big Data needs Team Work? /Parent 1 0 R 7 0 obj <> /Font << Predictive analytics is a set of advanced technologies that enable organizations to use data—both stored and real-time—to move This eBook explores the current Data Analytics industry and rounds off the top Big Data Analytics tools. 5 0 obj endobj >> endobj /T1_2 1 Tf /FontFile3 16 0 R [ (Caliendo) 10 (\054) 35 ( M\056\054) 35 ( \046 K) 25 (opeinig) -30 (\054) 35 ( S\056) 35 ( \0502008\051\056) 35 ( Some pr) 20 (actical guidance f) 15 (or the ) ] TJ -57.83 42.56 Td [ (to Gar) -15 (tner Inc) -40 (\056) 35 ( de\037nes it as ) 70 (\223Big data is high v) 10 (olume\054) 35 ( high v) 10 (elocity) 45 (\054) 35 ( and\057) ] TJ stream /MediaBox [ 0 0 595.276 841.89 ] [ (R) 32 (osenbaum\054) 35 ( P) 45 (\056R\056\054) 35 ( \046 Rubin\054) 35 ( D) 30 (\056) 35 ( B\056) 35 ( \0501983\051\056) 35 ( ) 70 (T) 15 (he centr) 20 (al r) 10 (ole of the pr) 10 (opensity scor) 10 (e in ) ] TJ /T1_1 38 0 R endobj [ (banking and insur) 20 (ance\054) 35 ( def) 15 (ence and secur) 10 (ity) 45 (\056) 35 ( ) ] TJ (70) Tj ARE YOU THERE YET? During the 19th National Congress of the Chinese Communist Party in October 2017, Chinese President Xi Jinping emphasized the need to This big data is gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. 0.216 0.773 0.969 rg 200.52 0 Td [ (to enable enhanced decision making) -30 (\054) 35 ( insight disco) 15 (v) 10 (ery and pr) 10 (ocess ) ] TJ In this data science beginner's guide, you can learn data science basics to begin your data … <>/Metadata 1915 0 R/ViewerPreferences 1916 0 R>> >> BDC 1 0.67 0 0.23 k [ (the comple) 10 (xity of datasets and not necessar) 10 (il) 10 (y their siz) 5 (e\056) 35 ( ) 70 (\221V) 95 (ar) 10 (iety\222) 45 ( r) 10 (ef) 15 (er) 10 (s ) ] TJ /SMask /None endobj [ (to r) 10 (ealise the impor) -15 (tance of using this data f) 15 (or their gr) 10 (o) 15 (wth\056) 35 ( ) 70 (As a r) 10 (esult\054) 35 ( ) ] TJ <> /CropBox [ 0 0 595.276 841.89 ] endobj endobj [ ( ) -28 (\072 ) ] TJ 8.4 0 0 12 59.5275 26.6981 Tm 0 -1.576 TD /T1_4 13 0 R ���Љ��o63~�(t�����su�V�,]_�OH;��b��]��t�P�LÂ}U�FFnq���{���*F���7�4?% BT 0 G [ (in the data w) 10 (hic) -10 (h can be used f) 15 (or v) 25 (ar) 10 (ious pur) 20 (poses suc) -10 (h as impr) 10 (o) 15 (ving ) ] TJ ( ) Tj >> BT /T1_1 1 Tf endobj /Flags 32 /T1_2 1 Tf Q BT [ (F) 40 (acebook and ) 70 (T) 50 (witter\051 f) 15 (or mark) 15 (et gr) 10 (o) 15 (wth and br) 20 (and manag) 15 (ement\056) 35 ( Some ) ] TJ mastering big data analytics—the use of computers to make sense of large data sets. 510.236 0 l T* 57% increase in big data specialists 243% 2012 2017 BIG DATA OPPORTUNITIES Today big data analytics oer or ganisations (A) Tj /Rotate 0 Big Data Analytics lässt sich in einzelne Teilgebiete gliedern. >> 16 0 obj /GS0 12 0 R endobj /Rotate 0 /BM /Normal i�|nn]�7(�f�`J�йx�.hϞ�R�A9v{L��Q��fP)r/LӋ�Х��t{&��� /OP true 0 g 11 0 obj /ArtBox [ 0 0 595.276 841.89 ] 13 0 0 13 311.811 397.9869 Tm 0 -1.576 TD 0 -1.576 TD 34.772 26.299 Td [ <0037004b004c0056> -278 <004c0056> -278 <0044> -277 <0056004c0051004a004f0048> -278 <004400550057004c0046004f0048> -278 <0049005500520050> ] TJ /TT2 74 0 R Big Data analytics is the process of inspecting, cleaning, transforming, and modeling Big Data to discover and communicate useful information and patterns, suggest conclusions, and support decision making. T* In this tutorial, we will discuss the most fundamental concepts and methods of Big Data Analytics. Collection of logs from many sources-In this step, the collection of data takes places from different sources. /op true >> 0.4 0.4 0.4 rg 13 0 obj 18 0 obj -1.031 -1.576 Td EMC /Resources << Please Note: There is a membership site you can get UNLIMITED BOOKS, ALL IN … /BaseFont /XSWKMI+Bliss-Bold << [ (\056\054) 35 ( ) ] TJ W Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations Yichuan Wanga,⁎, LeeAnn Kungb, Terry Anthony Byrda a Raymond J. Harbert College of Business, Auburn University, 405 W. Magnolia Ave., Auburn, AL 36849, USA b Rohrer College of Business, Rowan University, 201 Mullica Hill Road, Glassboro, NJ 08028, USA

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