synopsis on big data analytics pdf

/T1_2 1 Tf endobj /ActualText (��\000\011) [ (\0504\051\054) 35 ( 403\226425\056) ] TJ 0 -1.576 TD BT T* PDF - Open Access | Big Data Analytics and Its Applications endobj /T1_2 1 Tf /Resources << 0 0 595.275 841.89 re T* /FontFile3 16 0 R /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 ] /Font << 13 0 0 13 311.811 397.9869 Tm 1.134 -1.467 Td /Producer (PyPDF2) 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. [ (use of big data f) 15 (or the monitor) 10 (ing of social media \050f) 15 (or instance Link) 15 (edIn\054) 35 ( ) ] TJ Top big data analytics use cases Big data can benefit every industry and every organization. q /XHeight 473 /Parent 1 0 R ( ) Tj [ (J) 5 (our) -10 (nal of Economic S) 26 (ur) -35 (v) 15 (e) -10 (ys\054) ] TJ 0 0 595.276 841.89 re endobj 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/� /CropBox [ 0 0 595.276 841.89 ] /F1 7.97 Tf /Type /Page /GS0 gs >> /GS1 11 0 R /ca 1 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. 0 -1.467 TD T* [ (\056\054) 35 ( ) ] TJ 0 0 0 1 k 1.031 -1.576 Td /Type /Page We may no longer find a clear distinction on what is a Big Data Analytics problem and what is an AI problem. [ (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 Q endstream /TT2 74 0 R Explainability and interpretability: a model is explainable when its internal behaviour can be directly understood by humans (interpretability) or when explanations (justifications) can be [ (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 /T1_2 34 0 R During the 19th National Congress of the Chinese Communist Party in October 2017, Chinese President Xi Jinping emphasized the need to /Descent -236 -1.031 -1.576 Td [ (tw) 10 (o or mor) 10 (e GCSEs earl) 10 (y is bene\037cial to these students or not\056) ] TJ /C0_0 59 0 R 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. /T1_0 1 Tf 13 0 obj T* /BleedBox [ 0 0 595.276 841.89 ] /SMask /None /Rotate 0 [ (R) 41 (ef) 12 (er) 13 (ences) ] TJ endobj /Annots [ 57 0 R ] /Font << [ <004b005700570053001d00120012005a005a005a001100460044005000450055004c0047004a00480044005600560048005600560050004800510057001100520055004a00110058004e00120055004800560048004400550046004b0010> -62 <00500044005700570048005500560012> ] TJ endobj /T1_4 13 0 R [ (R) 24 (esear) 20 (c) -10 (h Division) ] TJ >> <> /Subtype /Type1C [ (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 >> >> /GS0 12 0 R /Length 4833 (Nadir Zanini ) Tj /BM /Normal 12 0 obj /OPM 1 /T1_2 1 Tf /BaseEncoding /WinAnsiEncoding But it’s of no value unless you know how to put your big data … 2 0 obj >> /ExtGState << <> >> BDC -1.031 -1.576 Td >> (35) Tj 0 0 m 0.378 0 Td [ (T) 15 (he concept of big data encompasses the collection of data\054) 35 ( the ) ] 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. [ <0011> ] TJ T* T* 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. /MediaBox [ 0 0 595.276 841.89 ] /T1_5 30 0 R /Parent 1 0 R ( ) Tj T* -57.83 42.56 Td Discover the top twenty-two use cases for big data. 96.56 0 Td 0 -1.576 TD T* /T1_4 1 Tf T* EMC 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 … /Length 14583 [ (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 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 0 -1.576 TD ��Љ��o63~�(t��su�V�,]_�OH;��b��]��t�P�LÂ}U�FFnq��{��*F��7�4?% <>/Metadata 1915 0 R/ViewerPreferences 1916 0 R>> ��?�,��!8[��p,�` ��8�UC%�� }!�G=F��X��H��)��:��,�]rЉ ��K'�;�f�&�K��u�@F��&��Z1-�ac�.�h\�Vk. q [ (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 /T1_4 25 0 R Organizations are capturing, storing, and analyzing data that has high volume, [ (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 [ (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 EMC q %�� 8.5 0 0 8.5 42.5197 502.2573 Tm /ProcSet [ /PDF /Text ] 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 /T1_5 1 Tf /T1_0 46 0 R >> BDC T* >> /T1_1 1 Tf /FontWeight 700 [ (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 [ (observ) 25 (ational studies f) 15 (or causal ef) 10 (f) 15 (ects\056) 35 ( ) ] TJ stream 200.52 0 Td BT /T1_3 42 0 R /T1_2 1 Tf /CropBox [ 0 0 595.276 841.89 ] Q stream /Parent 1 0 R T* [ (the amount of earl) 10 (y entry) 45 (\056) 35 ( Students will still be able to sit GCSEs in ) 85 (Y) 95 (ear ) ] TJ W -0.01 Tc on a) what big data is, b) how it can improve security analytics, and c) how it will — or won’t — integrate with SIEM. /Rotate 0 /T1_2 34 0 R [ (combination of data fr) 10 (om v) 25 (ar) 10 (ious sour) 20 (ces and under) 10 (standing patterns ) ] TJ 0 0 595.276 841.89 re endobj /T1_1 46 0 R 7 0 obj 10 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 14 0 obj /T1_0 1 Tf (36) Tj [ (to enable enhanced decision making) -30 (\054) 35 ( insight disco) 15 (v) 10 (ery and pr) 10 (ocess ) ] TJ >> BDC >> ARE YOU THERE YET? endobj [ (10\054) 35 ( but c) -10 (hang) 15 (es to accountability measur) 10 (es mean that onl) 10 (y the r) 10 (esult ) ] TJ >> /ArtBox [ 0 0 595.276 841.89 ] /T1_0 42 0 R 0 G /Metadata 77 0 R 1.134 -1.467 Td << (22) Tj 1 0 0 1 72 769.89 cm /Type /Catalog /F2 18 0 R I�t��T�"}NQ��zG��u�z��3s�2�J�"�-;&�~+��99�:�t��2�e�˿]'��=�M�^�g ��-�-ͭ�]��0��z� EMC /T1_2 1 Tf /OP false /T1_4 25 0 R /GS1 gs 1 0 0 1 0 0 cm /Type /FontDescriptor /SA true Why Big Data needs Team Work? We then move on to give some examples of the application area of big data analytics. /ArtBox [ 0 0 595.276 841.89 ] [ <008b> -278 <00380026002f00280036> -278 <0015001300140017> ] TJ /T1_2 1 Tf /GS1 11 0 R [ (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 0 -1.576 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 -0.03 Tc [ (the combination of v) 25 (ar) 10 (ious sour) 20 (ces of inf) 15 (ormation about pupils suc) -10 (h as ) ] TJ 8 0 obj /CS0 80 0 R Either way, big data analytics is how companies gain value and insights from data. ( ) Tj �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� � 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��@� q [ (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 [ (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 7 0 obj 0 -1.576 TD /Resources << /T1_2 1 Tf /Type /Page /BM /Normal 12 0 obj /TrimBox [ 0 0 595.276 841.89 ] 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. [ ( ) -28 (SUMMER ) -28 (2014) ] TJ 6 0 obj /CropBox [ 0 0 595.276 841.89 ] We start with defining the term big data and explaining why it matters. [ (\054) 35 ( 23\22640\056) ] TJ /MediaBox [ 0 0 595.276 841.89 ] /T1_4 1 Tf /T1_2 1 Tf Increasingly, big data feeds today’s advanced analytics endeavors such as artificial intelligence. /T1_2 34 0 R 0 -1.576 TD ( ) Tj Big Data has been used for advanced analytics in many domains but hardly, if … [ (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 /T1_3 42 0 R /GS1 gs /CapHeight 659 >> 0 0 0 0 k /GS0 gs Q endobj /GS2 87 0 R /GS0 12 0 R /T1_5 30 0 R 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. 1 0 0 0 k /ExtGState << endobj Q /MediaBox [ 0 0 595.276 841.89 ] <> Big Data Analytics Notes Pdf Download & List of Reference Books … 0 G 21 0 0 21 42.5197 467.2573 Tm 1.031 -1.576 Td Introduction Organizations are able to access more data today than ever before. /Resources << /CropBox [ 0 0 595.276 841.89 ] >> /ProcSet [ /ImageC /ImageB /Text /PDF /ImageI ] /T1_3 38 0 R /GS0 gs [ (Sociolo) 10 (gical M) 21 (ethods \046 R) 41 (esear) 15 (c) 10 (h\054) 20 ( ) ] TJ 20 0 obj 8.25 0 0 8.25 311.811 375.9869 Tm � �Fn8�BG}��>�:1��Z /Pages 1 0 R /Im0 85 0 R Amazon Web Services – Big Data Analytics Options on AWS Page 6 of 56 handle. Hence, big data analytics is really about two things—big data and analytics—plus how the two have teamed up to (and ) Tj /TT1 68 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 /FirstChar 30 [ (Intr) 10 (oduction) ] TJ /ActualText (��\000\011) <> endobj Enterprises can gain a competitive advantage by being early adopters of big data analytics. /BleedBox [ 0 0 595.276 841.89 ] <> [ (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 5) Make intelligent, data-driven decisions. /T1_1 46 0 R ( ) Tj %PDF-1.7 [ (V) 20 (ikas Dha) 20 (w) 25 (an ) ] 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_1 38 0 R [ (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 >> ET q /ArtBox [ 0 0 595.276 841.89 ] endobj 0 Tc 1.619 0 Td /Span << (A) Tj /GS1 11 0 R 9 0 0 9 42.5197 441.9187 Tm /Font << /T1_2 34 0 R T* << /T1_5 1 Tf /Encoding 14 0 R <> /Font << 0 -1.576 TD q << 0.4 0.4 0.4 rg [ (ISSUE ) -28 (18 ) ] TJ 57% increase in big data specialists 243% 2012 2017 BIG DATA OPPORTUNITIES Today big data analytics oer or ganisations (\057) Tj <> endobj 17 0 obj /T1_5 1 Tf /T1_3 1 Tf 0 -1.576 TD << /Contents 89 0 R /T1_2 34 0 R (M) Tj /TrimBox [ 0 0 595.276 841.89 ] /F1 50 0 R /CA 1 /ExtGState << /Filter /FlateDecode 8.4 0 0 12 59.5275 26.6981 Tm /T1_0 46 0 R Collection of logs from many sources-In this step, the collection of data takes places from different sources. This tutorial has been prepared for software professionals aspiring to learn the basics of Big Data Analytics. Predictive analytics is a set of advanced technologies that enable organizations to use data—both stored and real-time—to move /OP true [ (Psyc) 10 (holo) 10 (gical M) 21 (ethods\054) ] TJ 0 Tc n << endobj [ (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 ( ) Tj /ProcSet [ /PDF /Text ] /GS0 12 0 R 0 Tc (\174) Tj /ExtGState << Introduction to Big Data Analytics Big data analytics is where advanced analytic techniques operate on big data sets. This big data is gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. /T1_1 1 Tf 7 0 0 7 62.3666 27.6981 Tm /MC0 << /Span << [ (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 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�� [ (\0501\051\054) 35 ( 31\22672\056) ] TJ endobj [ (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 T* ( ) Tj /BleedBox [ 0 0 595.276 841.89 ] [ (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 /T1_0 1 Tf [ <0035004800560048004400550046004b> -277 <0030004400570057004800550056001d> -371 <0024> -277 <00260044005000450055004c0047004a0048> -278 <0024005600560048005600560050004800510057> -278 <005300580045004f004c004600440057004c00520051> ] TJ 0 Tc W /Span << /BleedBox [ 0 0 595.276 841.89 ] /ActualText (�� \010) [ (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 -1.134 -2 Td /Contents 88 0 R 0.4 0.4 0.4 rg S >> 5 0 obj 10 0 obj /T1_2 34 0 R /ProcSet [ /PDF /Text ] T* Q 13 /Contents 67 0 R /CropBox [ 0 0 595.276 841.89 ] /T1_3 1 Tf 0 g >> -57.83 52.02 Td /T1_6 30 0 R endobj This collected data has variety of nature, some might be structured [ (banking and insur) 20 (ance\054) 35 ( def) 15 (ence and secur) 10 (ity) 45 (\056) 35 ( ) ] TJ W >> endobj /MediaBox [ 0 0 595.276 841.89 ] -1.031 -1.576 Td /Type /ExtGState [ (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 endobj 0 -1.576 TD /Rotate 0 /GS1 11 0 R >> /Rotate 0 >> BDC 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. /ArtBox [ 0 0 595.276 841.89 ] This eBook explores the current Data Analytics industry and rounds off the top Big Data Analytics tools. <> 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. /MediaBox [ 0 0 595.276 841.89 ] T* 0 -1.576 TD [ (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 In this data science beginner's guide, you can learn data science basics to begin your data … [ 11 0 R] /Parent 1 0 R /T1_5 25 0 R 0 -1.576 TD 1 0 obj /GS0 12 0 R /Kids [ 3 0 R 4 0 R 5 0 R 6 0 R 7 0 R 8 0 R ] [ (to this\054) 35 ( w) 10 (e discuss ne) 10 (w f) 15 (orms of assessment suc) -10 (h as e\055assessment and ) ] TJ /StemV 120 endobj T* /T1_4 13 0 R /T1_5 1 Tf /T1_6 1 Tf The people who work on big data analytics are called data scientist these days and we explain what it encompasses. 0 g ( ) Tj /AIS false >> BDC 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. i�|nn]�7(�f�`J�йx�.hϞ�R�A9v{L��Q��fP)r/LӋ�Х��t{&�� /TrimBox [ 0 0 595.276 841.89 ] /Resources << 0 -1.576 TD /ActualText (a) <> 0.1 Tc >> [ (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 Big Data Analytics lässt sich in einzelne Teilgebiete gliedern. >> << [ (Biometr) -10 (ika\054) ] TJ <> /ItalicAngle 0 0.1 Tc [ (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 BT /FontName /XSWKMI+Bliss-Bold -0.01 Tc big data analytics follow for storage, analysis and maintenance [6] enumerated some of the basic procedures generally big data analytics follow. >> The need to analyze and leverage trend data collected by businesses is one of the main drivers for Big Data analysis tools. /T1_5 1 Tf /BaseFont /XSWKMI+Bliss-Bold /F1 7.97 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T* /T1_0 42 0 R >> /GS1 gs 11 0 obj << [ (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 /Im2 84 0 R 0 -1.576 TD 0 -1.576 TD [ (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 [ (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 (RESEARCH) Tj 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: 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 [ (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 /Font << /Contents 66 0 R Our bloggers have written several posts on this topic and how the use of data and analytics on those data is /T1_5 1 Tf /ProcSet [ /PDF /Text ] <> /Parent 1 0 R ET endobj /T1_2 1 Tf [ (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 7.5 0 0 7.5 42.5197 635.076 Tm [ (Pr) 10 (ospects and Pitf) 10 (alls in ) 70 (T) 15 (heory and Pr) 20 (actice\056) 35 ( ) ] TJ /Type /Pages /GS1 11 0 R Ten years ago, “big data analytics” was one of /Count 6 (9) Tj [ (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 q 0.4 0.4 0.4 RG /GS0 gs << /T1_1 38 0 R >> Click Download or Read Online Button to get Access Creating Value with Big Data Analytics ebook. 0 0 0 1 k 13 0 obj /T1_5 1 Tf <> >> 9 0 obj /Type /Page mastering big data analytics—the use of computers to make sense of large data sets. /T1_4 1 Tf In this tutorial, we will discuss the most fundamental concepts and methods of Big Data Analytics. 9 0 obj [ (\050BBC) -50 (\054) 35 ( 2013\073) 35 ( Lohr) 30 (\054) 35 ( 2012\051\056) 35 ( ) ] TJ /ExtGState << (Big data) Tj Big Data analytics – the process of analyzing and mining Big Data – can produce operational and business knowledge at an unprecedented scale and specificity. 0 g >> [ (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 << /Ascent 848 /T1_1 1 Tf Ebook. • – – – ata analytics is necessarily a Big d joint effort by researchers from academic institutions, government and society and industry. 7 0 0 7 42.5197 27.6981 Tm (Big data and social media analytics) Tj Further research could also estimate the average treatment effect for the treated in … >> ( ) Tj 0 g 0 -1.576 TD 0 -1.576 TD 244.42 52.02 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 -1.031 -1.576 Td stream /T1_6 25 0 R 1 0 0 1 42.5197 505.0053 cm 0.4 0.4 0.4 RG 6.5 0 0 6.5 42.5197 659.0757 Tm [ (impact\056) 35 ( Manc) -10 (hester\072) 35 ( Ofsted\056) ] TJ endobj 1.134 -1.467 Td endobj /Span << /GS0 12 0 R /LastChar 181 [ (A) -10 (pplications in the education industry mentioned in this ar) -15 (ticle include ) ] TJ >> BDC >> /ArtBox [ 0 0 595.276 841.89 ] 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 … -1.134 -2 Td T* /op false endobj /T1_5 30 0 R [ (\0501\051\054) 35 ( 3\22660\056) ] TJ 0 -1.576 TD [ (R) 41 (esear) 15 (c) 10 (h Matter) -15 (s\072) 25 ( ) 30 (A Cambr) -10 (idge ) 30 (Assessmen) 5 (t Publication\054) ] TJ (70) Tj 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 Costs remain high, there are great inefficiencies, and, for a large percentage of the population globally, access to care 0.55 0.19 0 0 k endobj [ (and using the r) 10 (esults so obtained\056) 35 ( Speci\037call) 10 (y) 45 (\054) 35 ( big data is a term used ) ] TJ 2016 BIG DATA THE WHATS, WHYS, AND HOWS OF DATA ANALYTICS BIG DATA ANALYTICS IS MAINSTREAM. (TT) Tj [ (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 14 0 obj The Big Data Analytics area evolves in a speed that was seldom seen in the history. <> /MediaBox [ 0 0 595.276 841.89 ] T* >> endobj >> 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 /Encoding /ActualText (ers) /T1_4 13 0 R /T1_2 1 Tf 1.134 -1.467 Td /Resources << /Type /Font /T1_2 1 Tf [ (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 ET << T* 0 -2.223 TD >> BT BT 0.275 0.095 0 0 K 0.1 Tc 11 0 obj /GS1 11 0 R /ArtBox [ 0 0 595.276 841.89 ] 4 0 obj /ToUnicode 17 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 /Type /Page 16 0 obj Our research indicates that China is aggressively working toward becoming a global leader in big data analytics. /F2 7.97 Tf ET 4.855 0 Td <> 1.031 -1.576 Td 8.25 0 0 8.25 42.5197 375.9869 Tm /TrimBox [ 0 0 595.276 841.89 ] [ (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 Since the dawn of the computer age, people have speculated about how humans would harness technology in the future. /T1_0 46 0 R 18 0 obj T* [ (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 /T1_3 38 0 R /T1_1 46 0 R >> 8.25 0 0 8.25 42.5197 793.0757 Tm /T1_2 1 Tf >> T* /Parent 1 0 R /CA 1 16 0 obj Last updated on Sep 21, 2020. T* T* endobj vernment and industry are The go sources of Big Data, and providers of problems and challenges, [ (in the ar) -15 (ticle\056) 35 ( ) ] TJ >> it is not all ﬁrms, just those recruiting big data sta. endobj 0 -1.576 TD [ (implementation of pr) 10 (opensity scor) 10 (e matc) -10 (hing) -30 (\056) 35 ( ) ] TJ 1 0.67 0 0.23 k Q 13 0 0 13 42.5197 397.9869 Tm /T1_5 13 0 R EMC endobj /ActualText (��\000\011) Summary: This chapter gives an overview of the field big data analytics. >> [ <0037004b004c0056> -278 <004c0056> -278 <0044> -277 <0056004c0051004a004f0048> -278 <004400550057004c0046004f0048> -278 <0049005500520050> ] TJ <> The model introduces a framework for converting data to actionable knowledge and mitigating potential risk to the [ (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 /Properties << /SMask /None /TrimBox [ 0 0 595.276 841.89 ] 0 g /AIS false >> endobj 2 0 obj ET endobj 8.468 0 Td 0 G /T1_1 38 0 R 0 -1.576 TD /T1_3 38 0 R (ERS) Tj /T1_1 1 Tf EMC BT <> /FontFamily (Bliss) (16) Tj Furthermore, its boundary with Artificial Intelligence becomes blurring. 0.216 0.773 0.969 rg /OPM 1 [ (monitor) 10 (ing and e) 10 (v) 25 (aluation of tests\056) ] TJ 0 -1.576 TD /TrimBox [ 0 0 595.276 841.89 ] %PDF-1.3 -1.134 -2 Td 510.236 0 l /CS1 78 0 R 0 -1.576 TD /Span << /T1_0 42 0 R << /ProcSet [ /PDF /Text /ImageC /ImageI ] Please Note: There is a membership site you can get UNLIMITED BOOKS, ALL IN … 8 0 obj /T1_3 42 0 R Analytics for big data is an emerging area, stimulated by advances in computer processing power, database technology, and tools for big data. endstream /Contents 58 0 R ˔��J� �Me� �>�-O��+O:��S^\~��@��K(��*ȿ��4�(��j��z��߽+�7�1��n��. /TT0 71 0 R 19 0 obj 4 0 obj -0.01 Tc /T1_5 30 0 R 0 G /FontStretch /Normal [ (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 3 0 obj /Differences [ 30 /fl /fi ] 0.216 0.773 0.969 RG 0 Tc [ (\0501\051\054) 35 ( 41\22655\056) ] TJ [ (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 /T1_1 1 Tf /T1_2 1 Tf 34.772 26.299 Td /Subtype /Type1 Zunächst stellt sich bei der Big Data Analytics die Aufgabe, riesige Datenmengen unterschiedlichen … /BleedBox [ 0 0 595.276 841.89 ] /Rotate 0 /T1_4 13 0 R /F1 7.97 Tf ( ) Tj /T1_5 1 Tf 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 -1.134 -2 Td /T1_2 1 Tf /Span << >> >> << /C0_0 59 0 R ET << [ (\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 Introduction to Data Science: A Beginner's Guide. /SA true n 14 w /FontBBox [ -55 -236 1193 848 ] 0 -1.467 TD [ ( ) -28 (\072 ) ] TJ 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. /XObject << Well-managed, trusted data leads to trusted analytics and trusted decisions. Big Data Analytics Overall Goals of Big Data Analytics in Healthcare Genomic Behavioral Public Health. /GS0 12 0 R 1 0 obj /Font << 0 G 0 Tc >> PDF Version Quick Guide Resources Job Search Discussion. endobj endobj /Rotate 0 /FontDescriptor 15 0 R 0 g << /Resources << [ (applications in v) 25 (ar) 10 (ious \037elds\054) 35 ( including education\056) 35 ( ) 85 (W) 45 (e also descr) 10 (ibe the ) ] TJ /T1_6 13 0 R /ExtGState << [ (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 6 0 obj (et al) Tj 0 0 0 1 k n endobj >> [ (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 endobj [ (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 15 0 obj 1.134 -1.467 Td /F1 7.97 Tf 0.55 0.19 0 0 k 5.346 0 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 3 0 obj /ColorSpace << endobj Big data analytics refers to the strategy of analyzing large volumes of data, or big data. /Contents 10 0 R [ (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 1.134 -1.467 Td <>/ExtGState<>/XObject<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/MediaBox[ 0 0 612 792] /Contents 4 0 R/Group<>/Tabs/S/StructParents 0>> << /Flags 32 0 -1.576 TD EMC tdwi.org 5 Introduction 1 See the TDWI Best Practices Report Next Generation Data Warehouse Platforms (Q4 2009), available on tdwi.org. /op true /Type /ExtGState 0 G /CropBox [ 0 0 595.276 841.89 ] 5 0 obj >> stream <> << Big Data Analytics Tutorial in PDF - You can download the PDF of this wonderful tutorial by paying a nominal price of $9.99. ( ) Tj /T1_5 1 Tf /T1_2 1 Tf Q 0 Tc 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. 0 -1.576 TD /Type /Page