-1.031 -1.576 Td <> [ (\050BBC) -50 (\054) 35 ( 2013\073) 35 ( Lohr) 30 (\054) 35 ( 2012\051\056) 35 ( ) ] TJ /F2 18 0 R /GS0 12 0 R endobj 20 0 obj /GS1 11 0 R 0 Tc endobj 8 0 obj /C0_0 59 0 R ET The model introduces a framework for converting data to actionable knowledge and mitigating potential risk to the 13 0 obj 1.134 -1.467 Td [ (\0501\051\054) 35 ( 3\22660\056) ] TJ [ (ISSUE ) -28 (18 ) ] 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 /ProcSet [ /PDF /Text ] >> (Big data and social media analytics) Tj /FontFamily (Bliss) stream 9 0 obj ( ) Tj /T1_2 1 Tf /XHeight 473 endobj We then move on to give some examples of the application area of big data analytics. /T1_5 25 0 R ˔���J� �Me� �>�-O�����+O:��S^\~��@��K(����*ȿ��4�(��j���z��߽+�7�1��n����. 12 0 obj 5) Make intelligent, data-driven decisions. /OP true -57.83 42.56 Td 0 -1.576 TD This eBook explores the current Data Analytics industry and rounds off the top Big Data Analytics tools. 13 0 0 13 42.5197 397.9869 Tm endobj /GS1 gs /T1_0 46 0 R >> [ <008b> -278 <00380026002f00280036> -278 <0015001300140017> ] TJ << endobj /T1_5 1 Tf /GS1 gs /T1_2 34 0 R /GS1 11 0 R /AIS false /Parent 1 0 R T* T* /T1_2 1 Tf /ArtBox [ 0 0 595.276 841.89 ] >> /Font << endobj >> [ (as healthcar) 10 (e and other scienti\037c r) 10 (esear) 20 (c) -10 (h\054) 35 ( comple) 10 (x man) 10 (uf) 10 (actur) 10 (ing ) ] TJ /Type /Page 0 -1.576 TD 0 -1.576 TD endobj /T1_5 1 Tf endobj Q [ (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 0 0 0 0 k R��(�yyN����n];����^��+ _��L�_T눑�xt�~W�>ioW>@Xϡ��ǿ���L������9_�чs��x��]�(%�R{���9�{�$� 7~��5��,��J��4��6G��,S��n�ؾ�_��H\�������p����@� ( ) Tj [ (Biometr) -10 (ika\054) ] TJ /T1_2 1 Tf Die wichtigsten davon sind: Die Datenbeschaffung aus verschiedenen Quellen mithilfe von Suchabfragen, die Optimierung und Auswertung der gewonnenen Daten sowie; die Analyse der Daten und Präsentation der Ergebnisse. endobj 1.031 -1.576 Td >> BDC x��] �dWY��j�����^��U�LwO�������$� 1#I&�qHȘe2a��$d'd##p��z�=ǣ�]�� Fp'�McT�`���z���{_�{�=[��ܓ����}�����oU3&�EQ�V���2�\-W�*M,֦�j��`T��*�k��Ly2�.�#I��e�Xq����}���o�H�K�]�E;�lh�5 �$z����"�|�8�6桓�~�ͥ\m[R%T�?l��7����t�C�x�R[��g��r�w$ruO jn�Vk �I�5S���,���Tv�'�*�J��ZR���迅�����9�>s�O���*N�i��c�ZaW�sG�E�1W�Z5n��V2Ŗ7�[t+}�Rk�b�_���.��Z�$US�ϔĩ0�O�m�NO(�+L,��fک5�n�Z�9��j�u�c�k�� ��0��g��g��K�����Z,�\]���|�8r:���80����u{��b��UZ+�D��˞��W�\ޤu4q1�q-�U�$� F�:mP� �jSw�����|q$��'؝n�.O�n�@��ֶ��M@�-4P�L�z�Z�q��p]���>8�D���[ANg��d���"DPur�,��B}�Y�B1�Tm�Z����e�h0���b9 c��,�/V�bc�6#> W���������yhuz-���G��cي����p�[s(��sD�Zߖ�T���(a�:_(N�)�Q���;��ѮQ ��� F0���,�=�K�$����R �a,]6�Z�~6�Z���x��y��Z�g �q��p{J�E隳���K�'e�9���Z��N�B�׬�����r}�: ��.v�� /Widths [ 619 601 238 0 0 0 0 894 0 0 347 347 0 0 231 363 231 394 542 542 542 542 542 542 542 542 542 542 231 0 556 592 0 0 0 626 539 608 668 475 467 681 695 255 331 578 432 797 729 745 502 745 563 501 539 684 0 949 0 586 0 0 0 0 0 0 0 494 528 446 530 496 347 504 536 260 270 485 270 832 539 544 529 534 363 418 385 534 487 751 490 523 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 235 410 424 0 500 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 542 ] Zunächst stellt sich bei der Big Data Analytics die Aufgabe, riesige Datenmengen unterschiedlichen … Introduction to Data Science: A Beginner's Guide. 16 0 obj We start with defining the term big data and explaining why it matters. Q /GS0 12 0 R /Span << [ (to enable enhanced decision making) -30 (\054) 35 ( insight disco) 15 (v) 10 (ery and pr) 10 (ocess ) ] TJ 0.4 0.4 0.4 rg /GS1 11 0 R x���Ko�@����hW�zf��EB�$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 Tc -0.01 Tc Our research indicates that China is aggressively working toward becoming a global leader in big data analytics. /TrimBox [ 0 0 595.276 841.89 ] >> /SMask /None /Type /Encoding Our bloggers have written several posts on this topic and how the use of data and analytics on those data is 3 0 obj /T1_3 42 0 R 244.42 52.02 Td (22) Tj T* <> 5 0 obj ( ) Tj 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. Increasingly, big data feeds today’s advanced analytics endeavors such as artificial intelligence. /Rotate 0 [ (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 Big data analytics refers to the strategy of analyzing large volumes of data, or big data. Since the dawn of the computer age, people have speculated about how humans would harness technology in the future. <> BT /GS0 12 0 R /TrimBox [ 0 0 595.276 841.89 ] 11 0 obj [ (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 /T1_4 13 0 R /ActualText (��\000\011) /T1_2 1 Tf <>/ExtGState<>/XObject<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/MediaBox[ 0 0 612 792] /Contents 4 0 R/Group<>/Tabs/S/StructParents 0>> 0 -1.576 TD endobj (35) Tj endobj 0 G [ (\0501\051\054) 35 ( 41\22655\056) ] TJ T* Organizations are capturing, storing, and analyzing data that has high volume, /T1_0 1 Tf 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. <> >> BDC endobj 4 0 obj I�t��T�"}NQ���zG��u�z����3s�2�J�"�-;&�~+��99�:�t��2�e�˿]'����=�M�^�g ���-�-ͭ�]������0��z� /ItalicAngle 0 0 -1.576 Td /T1_1 1 Tf -1.134 -2 Td >> (\174) Tj <> 0 0 595.276 841.89 re /OPM 1 /Parent 1 0 R /F1 7.97 Tf T* >> /Font << q /ArtBox [ 0 0 595.276 841.89 ] /T1_3 38 0 R /ProcSet [ /PDF /Text ] endobj /Rotate 0 [ (T) 15 (he concept of big data encompasses the collection of data\054) 35 ( the ) ] TJ 510.236 0 l -1.031 -1.576 Td endobj [ (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 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. Big Data Analytics Notes Pdf Download & List of Reference Books … (M) Tj W ( ) Tj >> /T1_2 1 Tf >> [ (\056\054) 35 ( ) ] TJ (A) Tj /F2 7.97 Tf /T1_5 1 Tf /Contents 88 0 R This collected data has variety of nature, some might be structured /Length 14583 endobj <> q 0 -1.576 TD [ (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 /T1_2 1 Tf /T1_0 42 0 R << /FontName /XSWKMI+Bliss-Bold (Big data) Tj << 0.4 0.4 0.4 rg 0 -1.576 TD /Type /FontDescriptor /ActualText (a) T* /SMask /None /TrimBox [ 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 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. >> /op true 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. 5 0 obj /Pages 1 0 R >> • – – – ata analytics is necessarily a Big d joint effort by researchers from academic institutions, government and society and industry. 0.216 0.773 0.969 RG >> �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� � /Kids [ 3 0 R 4 0 R 5 0 R 6 0 R 7 0 R 8 0 R ] /Span << 10 0 obj 2016 BIG DATA THE WHATS, WHYS, AND HOWS OF DATA ANALYTICS BIG DATA ANALYTICS IS MAINSTREAM. /T1_0 42 0 R << /Resources << /CS1 78 0 R /FontWeight 700 0 -1.576 TD >> >> (et al) Tj The need to analyze and leverage trend data collected by businesses is one of the main drivers for Big Data analysis tools. 0 0 595.275 841.89 re n [ (applications in v) 25 (ar) 10 (ious \037elds\054) 35 ( including education\056) 35 ( ) 85 (W) 45 (e also descr) 10 (ibe the ) ] TJ ARE YOU THERE YET? 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 /GS2 87 0 R %PDF-1.3 /Contents 58 0 R W /MediaBox [ 0 0 595.276 841.89 ] 7 0 0 7 62.3666 27.6981 Tm 17 0 obj /GS0 12 0 R 0.4 0.4 0.4 RG /T1_0 46 0 R Discover the top twenty-two use cases for big data. /Type /Page << /T1_4 1 Tf big data analytics follow for storage, analysis and maintenance [6] enumerated some of the basic procedures generally big data analytics follow. 0 g /T1_2 1 Tf >> Purpose – The purpose of this paper is to provide a conceptual model for the transformation of big data sets into actionable knowledge. /Type /Font 1 0 0 1 0 0 cm 8 0 obj /T1_4 1 Tf /T1_4 13 0 R /FirstChar 30 T* /GS1 11 0 R /Span << /T1_2 34 0 R /BleedBox [ 0 0 595.276 841.89 ] Big Data Analytics lässt sich in einzelne Teilgebiete gliedern. >> [ (10\054) 35 ( but c) -10 (hang) 15 (es to accountability measur) 10 (es mean that onl) 10 (y the r) 10 (esult ) ] TJ 0 Tc /T1_5 1 Tf /Ascent 848 /GS0 gs [ (J) 5 (our) -10 (nal of Economic S) 26 (ur) -35 (v) 15 (e) -10 (ys\054) ] TJ [ (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 >> [ (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 8.25 0 0 8.25 42.5197 793.0757 Tm 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 [ (R) 41 (ef) 12 (er) 13 (ences) ] TJ 9 0 obj Top big data analytics use cases Big data can benefit every industry and every organization. 14 0 obj endobj /Descent -236 >> [ (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 15 0 obj 0 -1.467 TD 10 0 obj /AIS false <> /TT1 68 0 R /TrimBox [ 0 0 595.276 841.89 ] (TT) Tj T* 0 Tc /GS0 gs /ArtBox [ 0 0 595.276 841.89 ] [ (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 /Span << /T1_1 1 Tf /Subtype /Type1C 0 Tc /ExtGState << [ (implementation of pr) 10 (opensity scor) 10 (e matc) -10 (hing) -30 (\056) 35 ( ) ] TJ /TrimBox [ 0 0 595.276 841.89 ] 0 g endobj << ( ) Tj /T1_2 1 Tf 5.346 0 Td /CropBox [ 0 0 595.276 841.89 ] /SA true /Rotate 0 endobj Collection of logs from many sources-In this step, the collection of data takes places from different sources. [ (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 8.25 0 0 8.25 311.811 375.9869 Tm /Flags 32 0 -1.576 TD (and ) Tj /StemV 120 0.378 0 Td n /Resources << The Big Data Analytics area evolves in a speed that was seldom seen in the history. /MC0 << /ActualText (ers) /TrimBox [ 0 0 595.276 841.89 ] 8.5 0 0 8.5 42.5197 502.2573 Tm T* /BleedBox [ 0 0 595.276 841.89 ] (16) Tj /T1_2 1 Tf /T1_1 38 0 R q But it’s of no value unless you know how to put your big data … /T1_1 38 0 R 0.55 0.19 0 0 k [ (\0504\051\054) 35 ( 403\226425\056) ] TJ [ (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 /T1_5 1 Tf (ERS) Tj [ (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 0 0 595.276 841.89 re Predictive analytics is a set of advanced technologies that enable organizations to use data—both stored and real-time—to move T* 12 0 obj 19 0 obj [ (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 3 0 obj /Differences [ 30 /fl /fi ] <> [ <0035004800560048004400550046004b> -277 <0030004400570057004800550056001d> -371 <0024> -277 <00260044005000450055004c0047004a0048> -278 <0024005600560048005600560050004800510057> -278 <005300580045004f004c004600440057004c00520051> ] TJ endobj vernment and industry are The go sources of Big Data, and providers of problems and challenges, /CropBox [ 0 0 595.276 841.89 ] 1 0 obj /Type /Page 0 G /Parent 1 0 R <> /T1_2 34 0 R 8.25 0 0 8.25 42.5197 375.9869 Tm 0.1 Tc /Metadata 77 0 R 1 0 0 1 42.5197 505.0053 cm [ (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 [ (the combination of v) 25 (ar) 10 (ious sour) 20 (ces of inf) 15 (ormation about pupils suc) -10 (h as ) ] TJ /Im2 84 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 >> /T1_6 13 0 R /T1_2 1 Tf %PDF-1.7 T* /CropBox [ 0 0 595.276 841.89 ] /T1_5 1 Tf Audience. 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Note: There is a membership site you can get UNLIMITED BOOKS, ALL IN … /T1_1 46 0 R ET /Rotate 0 /BleedBox [ 0 0 595.276 841.89 ] T* -1.134 -2 Td [ (Pr) 10 (ospects and Pitf) 10 (alls in ) 70 (T) 15 (heory and Pr) 20 (actice\056) 35 ( ) ] TJ endobj [ (2011\051\056) 35 ( ) 70 (A w) 10 (ell\055kno) 15 (wn model \050) -10 (kno) 15 (wn as 3V\222) 25 (s model\051 of big data attr) 10 (ibuted ) ] TJ [ (in man) 15 (y ar) 10 (eas\054) 35 ( including education\056) 35 ( In simple terms it r) 10 (ef) 15 (er) 10 (s to the ) ] TJ /T1_5 1 Tf [ (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 0 0 0 1 k /Span << EMC 0.55 0.19 0 0 k /CropBox [ 0 0 595.276 841.89 ] PDF Version Quick Guide Resources Job Search Discussion. >> [ (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 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. /CropBox [ 0 0 595.276 841.89 ] W /CapHeight 659 1.134 -1.467 Td /GS0 12 0 R 0 -2.223 TD endobj [ (tw) 10 (o or mor) 10 (e GCSEs earl) 10 (y is bene\037cial to these students or not\056) ] 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 << /ca 1 T* /T1_0 42 0 R /BleedBox [ 0 0 595.276 841.89 ] [ (\054) 35 ( 23\22640\056) ] TJ ��?�,����!8[���p,�` ��8�UC%�� }!�G=F���X�����H���)���:��,�]rЉ ��K'�;�f�&�K��u�@F��&��Z1-�ac�.�h\�Vk. 13 0 0 13 311.811 397.9869 Tm /ExtGState << -0.01 Tc [ (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 /FontFile3 16 0 R [ (observ) 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obj /T1_2 1 Tf T* [ (R) 24 (esear) 20 (c) -10 (h Division) ] TJ /T1_0 1 Tf /Type /Page ET 1.134 -1.467 Td Click Download or Read Online Button to get Access Creating Value with Big Data Analytics ebook. endobj Q /T1_3 38 0 R /CA 1 7.5 0 0 7.5 42.5197 635.076 Tm ( ) Tj 0 -1.576 TD ( ) Tj /Font << endobj [ (cannot be ef\037cientl) 10 (y handled b) 15 (y tr) 20 (aditional data pr) 10 (ocessing softw) 25 (ar) 10 (e ) ] TJ /T1_0 1 Tf /Type /Page � �Fn8�BG}��>�:1��Z /ExtGState << This tutorial has been prepared for software professionals aspiring to learn the basics of Big Data Analytics. 21 0 0 21 42.5197 467.2573 Tm /TT2 74 0 R 200.52 0 Td [ (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 0 -1.576 TD /T1_4 25 0 R -0.03 Tc 2 0 obj /Font << 0 0 0 1 k endobj /MediaBox [ 0 0 595.276 841.89 ] 0.4 0.4 0.4 RG /ca 1 /T1_1 1 Tf /Resources << /T1_1 1 Tf >> endstream endobj 4 0 obj [ (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 EMC 0 -1.576 TD /ArtBox [ 0 0 595.276 841.89 ] >> [ (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 << >> /FontDescriptor 15 0 R /T1_5 1 Tf >> BDC 57% increase in big data specialists 243% 2012 2017 BIG DATA OPPORTUNITIES Today big data analytics oer or ganisations 1.031 -1.576 Td <> 1 0.67 0 0.23 k Big Data has been used for advanced analytics in many domains but hardly, if … /T1_3 38 0 R /Contents 67 0 R <> -1.031 -1.576 Td Q 0 -1.467 TD /Im1 85 0 R /MediaBox [ 0 0 595.276 841.89 ] 0.1 Tc /ArtBox [ 0 0 595.276 841.89 ] /T1_4 25 0 R 0 -1.576 TD [ (Intr) 10 (oduction) ] TJ The people who work on big data analytics are called data scientist these days and we explain what it encompasses. /FontBBox [ -55 -236 1193 848 ] [ <004b005700570053001d00120012005a005a005a001100460044005000450055004c0047004a00480044005600560048005600560050004800510057001100520055004a00110058004e00120055004800560048004400550046004b0010> -62 <00500044005700570048005500560012> ] TJ Either way, big data analytics is how companies gain value and insights from data. >> (70) Tj 0 G [ (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 ( ) Tj [ (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 stream /Parent 1 0 R During the 19th National Congress of the Chinese Communist Party in October 2017, Chinese President Xi Jinping emphasized the need to endobj 34.772 26.299 Td /T1_5 30 0 R [ (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 /Annots [ 57 0 R ] [ (combination of the data collected fr) 10 (om v) 25 (ar) 10 (ious sour) 20 (ces\054) 35 ( pr) 10 (ocessing it ) ] TJ 0 -1.576 TD <> >> [ (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 /Type /Catalog T* [ (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 /GS0 gs Explainability and interpretability: a model is explainable when its internal behaviour can be directly understood by humans (interpretability) or when explanations (justifications) can be 1.134 -1.467 Td EMC /LastChar 181 0 -1.576 TD [ (combination of data fr) 10 (om v) 25 (ar) 10 (ious sour) 20 (ces and under) 10 (standing patterns ) ] TJ >> /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 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 … /Font << [ (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 0 0 0 1 k [ (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 1.134 -1.467 Td [ (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_2 1 Tf 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. /Rotate 0 [ (R) 41 (esear) 15 (c) 10 (h Matter) -15 (s\072) 25 ( ) 30 (A Cambr) -10 (idge ) 30 (Assessmen) 5 (t Publication\054) ] TJ 0 Tc S /F1 7.97 Tf /T1_0 46 0 R (9) Tj >> /Contents 89 0 R /BleedBox [ 0 0 595.276 841.89 ] /CS0 80 0 R /T1_2 1 Tf [ (Psyc) 10 (holo) 10 (gical M) 21 (ethods\054) ] TJ /op false endobj [ (to this\054) 35 ( w) 10 (e discuss ne) 10 (w f) 15 (orms of assessment suc) -10 (h as e\055assessment and ) ] TJ /ActualText (��\000\011) 0 g Enterprises can gain a competitive advantage by being early adopters of big data analytics. /ExtGState << %���� 0 -1.576 TD /Resources << -1.031 -1.576 Td [ (\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 0 -1.576 TD /T1_5 1 Tf [ (and using the r) 10 (esults so obtained\056) 35 ( Speci\037call) 10 (y) 45 (\054) 35 ( big data is a term used ) ] TJ T* 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. /Filter /FlateDecode /T1_4 13 0 R 0 0 m T* 0.1 Tc 8.4 0 0 12 59.5275 26.6981 Tm >> endobj /MediaBox [ 0 0 595.276 841.89 ] /C0_0 59 0 R /Length 4833 /T1_1 38 0 R 1.134 -1.467 Td [ (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 7 0 obj 96.56 0 Td << T* (\057) Tj Amazon Web Services – Big Data Analytics Options on AWS Page 6 of 56 handle. /Type /ExtGState T* << <> /T1_2 34 0 R n 7 0 0 7 42.5197 27.6981 Tm /Parent 1 0 R /Span << (RESEARCH) Tj it is not all firms, just those recruiting big data sta. EMC >> Well-managed, trusted data leads to trusted analytics and trusted decisions. /Rotate 0 /ExtGState << 18 0 obj /BleedBox [ 0 0 595.276 841.89 ] ET 0 -1.576 TD [ (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 [ ( ) -28 (SUMMER ) -28 (2014) ] TJ 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. BT [ (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 /ProcSet [ /PDF /Text /ImageC /ImageI ] BT /T1_2 1 Tf /SA true [ (in the ar) -15 (ticle\056) 35 ( ) ] TJ << endobj endobj << >> Last updated on Sep 21, 2020. /ProcSet [ /PDF /Text ] 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. T* Why Big Data needs Team Work? >> BDC 1.031 -1.576 Td [ (\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 2 0 obj [ (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 7 0 obj /ArtBox [ 0 0 595.276 841.89 ] BT /Parent 1 0 R [ (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 8.468 0 Td Introduction Organizations are able to access more data today than ever before. [ (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 0 G 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. [ 11 0 R] Hence, big data analytics is really about two things—big data and analytics—plus how the two have teamed up to /CropBox [ 0 0 595.276 841.89 ] /Type /ExtGState endobj 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 >> This big data is gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. 0 g 14 0 obj /T1_5 30 0 R /ToUnicode 17 0 R Summary: This chapter gives an overview of the field big data analytics. /Properties << /ExtGState << /F1 7.97 Tf >> BDC /GS1 11 0 R 0 g -57.83 52.02 Td /FontStretch /Normal /ActualText (��\000\011) Ten years ago, “big data analytics” was one of Ebook. 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/� 6 0 obj T* [ (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 q /Type /Page 0 G ET /ProcSet [ /PDF /Text ] (Nadir Zanini ) Tj /BaseFont /XSWKMI+Bliss-Bold /ProcSet [ /ImageC /ImageB /Text /PDF /ImageI ] [ (monitor) 10 (ing and e) 10 (v) 25 (aluation of tests\056) ] TJ [ (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 /CA 1 /OP false 6.5 0 0 6.5 42.5197 659.0757 Tm /T1_3 42 0 R endobj [ (\0501\051\054) 35 ( 31\22672\056) ] TJ ( ) Tj 0 -1.576 TD /T1_3 42 0 R New Software and Hardware tools are emerging and disruptive. 0 -1.576 TD 0.275 0.095 0 0 K stream endobj (36) Tj 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 … In this data science beginner's guide, you can learn data science basics to begin your data … <> [ (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 /Contents 10 0 R on a) what big data is, b) how it can improve security analytics, and c) how it will — or won’t — integrate with SIEM. /T1_5 1 Tf Q ET /Type /Pages ���Љ��o63~�(t�����su�V�,]_�OH;��b��]��t�P�LÂ}U�FFnq���{���*F���7�4?% [ <0011> ] TJ /BaseEncoding /WinAnsiEncoding q /T1_2 1 Tf [ <0037004b004c0056> -278 <004c0056> -278 <0044> -277 <0056004c0051004a004f0048> -278 <004400550057004c0046004f0048> -278 <0049005500520050> ] TJ /ColorSpace << 15 0 obj >> Furthermore, its boundary with Artificial Intelligence becomes blurring. /T1_6 30 0 R /GS0 gs 0 -1.576 TD /T1_1 1 Tf 0.1 Tc 4.855 0 Td Big Data Analytics Overall Goals of Big Data Analytics in Healthcare Genomic Behavioral Public Health. [ (small\054) 35 ( ar) 10 (e implementing \050or planning to implement\051 big data str) 20 (ateg) 15 (ies\056) 35 ( ) ] TJ /T1_3 1 Tf mastering big data analytics—the use of computers to make sense of large data sets. Analytics for big data is an emerging area, stimulated by advances in computer processing power, database technology, and tools for big data. /Resources << -1.134 -2 Td << /T1_5 30 0 R We may no longer find a clear distinction on what is a Big Data Analytics problem and what is an AI problem. >> <>/Metadata 1915 0 R/ViewerPreferences 1916 0 R>> 0 -1.576 TD /BM /Normal 0 g [ (V) 20 (ikas Dha) 20 (w) 25 (an ) ] TJ In this tutorial, we will discuss the most fundamental concepts and methods of Big Data Analytics. Costs remain high, there are great inefficiencies, and, for a large percentage of the population globally, access to care BT /GS0 12 0 R Further research could also estimate the average treatment effect for the treated in … T* /MediaBox [ 0 0 595.276 841.89 ] Introduction to Big Data Analytics Big data analytics is where advanced analytic techniques operate on big data sets. 14 w /TT0 71 0 R >> >> >> BDC 1 0 0 0 k /Subtype /Type1 /XObject << PDF - Open Access | Big Data Analytics and Its Applications Q 1 0 obj <> i�|nn]�7(�f�`J�йx�.hϞ�R�A9v{L��Q��fP)r/LӋ�Х��t{&��� /Contents 66 0 R /Producer (PyPDF2) T* 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. /GS1 gs >> Top big data access more data today than ever before and Hardware tools are and., and HOWS of data Analytics just those recruiting big data Analytics are called data scientist these days we. 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