/P 121 0 R >> /K [ 16 ] /S /P endobj 207 0 obj /S /P 4) Manufacturing. /P 72 0 R /K [ 6 ] /Pg 54 0 R << We have all the data, … << /K 54 endobj endobj 182 0 obj $4�%�&'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz�������������������������������������������������������������������������� ? /S /TR /K [ 1 ] << endobj << 135 0 obj /Pg 3 0 R 140 0 obj 205 0 obj /S /Span << 162 0 obj /S /Span /P 72 0 R /P 72 0 R �T���c��ʩ�~S��_$*P�̅�:����EHW���;�{�����|D� JH,�Tؐ�\�zL�� �0ʣtF�x�טX�≃��^C�aj2��h��Ӊ� u��I���!�{���z�a�jv���_[`�'��A�դ��٢�"~��m�y�|cN��RJԢ43���k�:��� �2h[�z�V�^�A�mxlG�x)��� ���r�J��v��:|ﺁoC�h�+�A?�2��ě�@I[G��]ee�R��_,���=bc����*z���c�Z�(�J��}��"+�J�. 195 0 obj endobj << >> /S /P /P 231 0 R The applications of big data are endless. /S /Link >> /P 72 0 R << >> >> endobj /P 236 0 R /K [ 105 0 R 106 0 R 107 0 R ] /S /P 3) Banking. << /Pg 3 0 R /S /P endobj << Data (Big Data) generated by is ma- … >> << /P 72 0 R >> << /P 72 0 R With the help of predictive analytics, medical ... 2) Academia. /P 115 0 R >> /K [ 24 ] endobj /P 72 0 R /Pg 3 0 R /P 72 0 R /S /Span Individual solutions may not contain every item in this diagram.Most big data architectures include some or all of the following components: 1. /K [ 16 ] /K 56 << /S /Span /P 72 0 R /Pg 46 0 R endobj Data sources. >> << /P 236 0 R endobj These characteristics are often known as the V’s of Big Data. >> /S /P >> endobj /Pg 40 0 R /Pg 60 0 R endobj << /S /H2 endobj << endobj /S /Span /QuickPDFF192533e2 14 0 R << 156 0 obj /S /P 5) IT. << 101 0 obj /P 226 0 R /QuickPDFF3ccb7091 14 0 R << /Pg 3 0 R /K [ 250 0 R ] /K [ 11 ] View the article PDF and any associated supplements and figures for a period of 48 hours. /Pg 60 0 R PDF Version Quick Guide Resources Job Search Discussion. << /MediaBox [ 0 0 595.38 841.92 ] 169 0 obj endobj 184 0 obj /S /H2 >> >> /K [ 1 ] 246 0 obj 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 95 0 R 96 0 R 97 0 R 99 0 R 102 0 R 103 0 R 107 0 R >> /P 72 0 R 122 0 obj 84 0 obj Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. /S /P ... Big Data Analytics largely involves collecting data from different sources, munge it in a way that it becomes available to be consumed by analysts and finally deliver data … << << /Pg 54 0 R << endobj /K [ 23 ] >> /K [ 17 ] /K [ 11 ] /Pg 40 0 R /S /LI endobj >> /Annots [ 26 0 R 27 0 R 28 0 R 29 0 R 30 0 R 31 0 R 32 0 R 33 0 R 34 0 R ] /F2 7 0 R << 244 0 obj /K [ 15 ] endobj << /Pg 46 0 R /S /Span >> /S /Span 188 0 obj endobj << /Pg 46 0 R /P 161 0 R /Pg 46 0 R /Pg 3 0 R /S /P << << endobj /Pg 60 0 R /S /P /Pg 46 0 R /S /Span << �lk�_��ec_���Wb!��Q�S���r��Ns����bj���W��*�GeŪ��E%¤7f7�@bw�pX?�E�dǏ�P����'3��b ���Y^��,7�+;7/_���-�[�ȂG��MǢ��5-�6A{&���6"O� /QuickPDFFbc338050 7 0 R /Pg 46 0 R << /S /P >> /K [ 160 0 R 164 0 R ] endobj >> �� � } !1AQa"q2���#B��R��$3br� /Type /Action 196 0 obj /S /Span << This post will explain the 6 main characteristics of Big Data. /Obj 26 0 R << /P 72 0 R /K [ 6 ] >> 194 0 obj /Nums [ 0 74 0 R 1 77 0 R 2 81 0 R 3 84 0 R 4 100 0 R 5 104 0 R 6 104 0 R 7 109 0 R 8 109 0 R 239 0 obj << << /P 72 0 R << INTRODUCTION Big data is a collection of data sets or a combination of data sets. /Pg 46 0 R /Pg 3 0 R 131 0 obj >> /S /Span /S /Span /K [ 21 ] /Pg 46 0 R >> >> /K [ 15 ] 148 0 obj << /D [ 3 0 R /FitH 0 ] /Pg 3 0 R endobj endobj 117 0 obj 187 0 obj 133 0 obj /Pg 3 0 R 166 0 obj •Boeing 737 will generate 240 terabytes of flight data during a single flight across the US. /K [ 19 ] >> /P 72 0 R >> /QuickPDFFb2815db7 16 0 R << << /Pg 40 0 R /K [ 18 ] /S /P Characteristics of Big Data: Details: Volume: Organisations have to constantly scale their storage solutions since big data clearly requires large amount of space to be stored. endobj 95 0 obj >> /P 72 0 R %PDF-1.5 Following are some the examples of Big Data- The New York Stock Exchange generates about one terabyte of new trade data per day. /S /H2 /DisplayDocTitle false /S /H2 /S /P /S /Span /Pg 40 0 R << /QuickPDFF0e83ea2a 16 0 R 209 0 obj stream /Pg 60 0 R /P 72 0 R 109 0 obj /F5 16 0 R 147 0 R 148 0 R 149 0 R 150 0 R 151 0 R 152 0 R 153 0 R 154 0 R 155 0 R 156 0 R 157 0 R >> 153 0 obj /P 72 0 R /Pg 60 0 R /Pg 54 0 R << /QuickPDFFe8c7b1a7 7 0 R endobj /Pg 46 0 R /StructParents 0 115 0 obj << /Pg 60 0 R 217 0 R 218 0 R 219 0 R 220 0 R 221 0 R 222 0 R 223 0 R 225 0 R 226 0 R 253 0 R 254 0 R /K [ 5 ] /Pg 54 0 R /Pg 54 0 R /Length 25088 << /P 236 0 R /P 72 0 R 199 0 obj 142 0 obj /P 169 0 R /S /P endobj /K [ 9 ] /Pg 40 0 R /K [ 13 ] ... the characteristics of data in big data streams are unknown. /K [ 14 ] /S /P /Pg 54 0 R /K [ 5 ] /P 174 0 R /P 173 0 R /P 72 0 R << /Pg 54 0 R endobj /K [ 7 ] /Pg 3 0 R /Pg 40 0 R /Pg 60 0 R /Pg 3 0 R /P 72 0 R >> /S /TD /S /Span << We differentiate Big Data characteristics from traditional data by one or more of the four V’s: Volume, Velocity, Variety and variability.. 1. endobj /QuickPDFF67c671fd 62 0 R /Pg 54 0 R /Pg 60 0 R /Pg 3 0 R /S /Link /K [ 61 ] /P 98 0 R endobj /Pg 3 0 R >> /K 51 This paper presents an overview of Big Data's content, types, architecture, technologies, and characteristics of Big Data such as Volume, Velocity, Variety, Value, and Veracity. endobj /HideToolbar false endobj /K [ 20 ] endobj /P 72 0 R endobj >> /K [ 101 0 R 102 0 R ] endobj >> /K [ 126 0 R 127 0 R ] /S /TR endobj << endobj /P 72 0 R �� � w !1AQaq"2�B���� #3R�br� /QuickPDFFeb6d249b 12 0 R Big Data is generated at a very large scale and it is being used by many multinational companies to process and analyse in order to uncover insights and improve the business of many organisations. /Type /Group /P 72 0 R 259 0 obj 179 0 obj endobj /K [ 20 ] << /K [ 174 0 R 176 0 R ] endobj /S /LBody /K [ 10 ] endobj /P 226 0 R >> /K [ 17 ] /P 72 0 R Working towards this direction, this paper … 90 0 R 91 0 R 92 0 R 93 0 R 94 0 R 95 0 R 96 0 R 97 0 R 98 0 R 115 0 R 129 0 R 130 0 R 218 0 obj /Pg 40 0 R /P 159 0 R /K [ 122 0 R 123 0 R ] /S /TD /P 72 0 R 200 0 obj /K [ 12 13 ] /P 178 0 R /P 72 0 R /K [ 2 ] /K [ 16 ] The following diagram shows the logical components that fit into a big data architecture. endobj endobj /P 104 0 R /Filter /FlateDecode endobj endobj /K 52 /S /LI �p��Bo�� /K [ 11 ] /Width 701 >> /Type /OBJR /Pg 40 0 R /S /H2 << >> /K [ 7 ] >> << 139 0 obj �9ك4�A>�\^�l�������X��U�η�`�;����r��>�?J�3o[x��J��J��"���v�_�d��q�Erԁd�C�i�H�.�'�@���j��*M�Kx��o3l��T�G=wz��G:��EvT�+(�J�t��� |��쑣ܓC �!p�g?��Ef��۽���M8�^S�n������g�LJ��?4vlzx�t� d]���t��9y_�)c�|���W�) I˟Q��ؿ�*��:%^��^��Nr�z��tܘ�`p�R+!�����f�}�xeKY�؀nBL��=���@2��d���m��v $��E�k�,H 嫸� k,�d�� �X �i�C�3�G�����:݋'B&>��\�-R$��o @ ��z]Ѡz�{9 << /Pg 60 0 R 185 0 obj /Pg 40 0 R /P 72 0 R endobj << >> To achieve clarity and coherence in Big Data definition, Ylijoki & Porras suggested that data and its … /P 72 0 R >> ��Q�[�_��̨3����8�֩[EkeKy��ǯ��4�,��,�q��6o� 107 0 obj /P 72 0 R �F�(��(��(��(��(��(��(��(��(��(��(�[email protected]�'�E մ�R㑀� ~�*����8d��gX����x��a��y��\yx�6]�Em��� |]�D ��"'��ߘ`a���;n&�+����2�A~�� /Filter /DCTDecode << << /Obj 33 0 R /K [ 22 ] /K [ 0 ] /K 55 /Subtype /Image /PageLayout /SinglePage /Obj 34 0 R /P 243 0 R endobj >> /S /Span A text file is a few kilobytes, a sound file is a few megabytes while a full-length movie is a few gigabytes. /P 72 0 R /K [ 59 ] << /S /GoTo /S /Span 100 0 obj 237 0 obj 105 0 obj << /QuickPDFF72a0e729 35 0 R and a new three characteristics of big data has been explored further to handle big data efficiently. Big data systems are uniquely suited for surfacing difficult-to-detect patterns and providing insight into behaviors that are impossible to find through conventional means. /P 72 0 R >> << << Some then go on to add more Vs to the list, to also include—in my case—variability and value. /QuickPDFF0469100c 62 0 R /S /LBody endobj /P 72 0 R /P 72 0 R << >> size, they do not possess the other characteristics of Big Data. /Marked true /Pg 54 0 R endobj endobj /P 72 0 R 191 0 obj Let’s see how. /Pg 54 0 R endobj >> /P 72 0 R /Pg 60 0 R /K [ 20 ] /P 226 0 R << 171 0 obj In this … /P 249 0 R /S /P /K [ 10 ] 158 0 R 162 0 R 163 0 R 166 0 R 167 0 R 76 0 R ] endobj << /K 47 endobj 77 0 obj 150 0 obj /S /Link /QuickPDFF5c4c4d77 9 0 R /S /P 3 0 obj << This pushing the envelope on analysis is an exciting aspect of the big data analysis movement. >> /Tabs /S Social Media The statistic shows that 500+terabytes of new data get ingested into the databases of social media site Facebook, every day. /Pg 54 0 R endobj 212 0 obj /Pg 40 0 R /Type /Pages 232 0 obj >> /S /P /S /P /Type /XObject endobj /Pg 40 0 R [ 171 0 R 172 0 R 175 0 R 176 0 R 179 0 R 180 0 R 181 0 R 181 0 R 182 0 R 183 0 R /K [ 13 ] /P 72 0 R 134 0 obj << /S /H1 /Pg 60 0 R Velocity refers to the increasing speed at which big data is created and the increasing speed at which the data needs to be stored and analyzed. 176 0 obj /S /H1 /K [ 170 0 R 172 0 R ] endobj /P 72 0 R /S /P endobj endobj /Pg 46 0 R /S /Span 228 0 obj endobj /K [ 258 0 R 259 0 R ] This poses difficulty in selecting and allocating appropriate resources to big data stream. endobj /Pg 40 0 R /Obj 30 0 R << 206 0 obj endobj 78 0 obj /K [ 252 0 R ] /K [ 175 0 R ] << /Pg 3 0 R >> /Pg 46 0 R 225 0 obj /P 173 0 R 257 0 obj >> << endobj /P 165 0 R /K [ 42 ] 168 0 obj endobj /K [ 3 ] >> /P 72 0 R /Pg 3 0 R /P 160 0 R endobj endobj /K [ 13 ] /K [ 178 0 R 180 0 R ] /S /H2 224 0 obj /S /P endobj >> /K [ 166 0 R ] 0:18 Big data plays a part in all of that. << 241 0 obj >> 248 0 obj /K [ 237 0 R 238 0 R 242 0 R 243 0 R 246 0 R ] >> /K [ 18 ] >> /S /P endobj /P 238 0 R /K [ 21 ] /P 72 0 R /QuickPDFFf2054904 18 0 R 163 0 obj >> 219 0 R 220 0 R 221 0 R 222 0 R 83 0 R ] ��0GC�ar�5�q~�����3Q�o�D]ÿ2I���{��Y��g��>ω|�:��E��~ �m��+�ߙĥ)�~闢n�Rׁ�R�rn�{�8AU���^c&�(��]��p���c�P��~�����猪H���)?��*��>r� #�Μ�]��pb2�,0�@�u�&R)�00�6���]-7�������ir�E=)�xʰ��!F`XV�1�;��@8��3�v�om���}��5�{��2_�)q�ٽAHy���� endobj /Pg 54 0 R /K [ 3 ] endobj /Pg 46 0 R 96 0 obj /K [ 228 0 R ] >> �6Y����C�}GA���!����P�t;RЎ渋�.S$�_T2N�R#2,���BhƬ ��G3��H��$Ȑ��������z#ppl/���u�5��)..�U�l�Rq�Dm�X�N&.|n;Qe3! /K 44 /Lang (en-US) /Pg 3 0 R << /Pg 40 0 R /Pg 60 0 R endobj /Pg 60 0 R >> >> << /Pg 40 0 R 143 0 obj >> =3�{�y�3ݨ����[����.9�s1(i�c�RP�F����0)F� endobj /P 164 0 R Index Terms — Big Data, Hadoop, Framework, HDFS, Big Data Components, 3 V’s, Big Data Characteristics, Hive. /S /Link >> /P 226 0 R 251 0 obj >> /P 98 0 R 0:30 The size of the data helps to define whether it can 0:32 actually be considered big data. << /PageMode /UseNone 104 0 obj << endobj /K [ 12 ] /S /Span /P 72 0 R The volume of data that one has to deal has exploded to unimaginable levels in the past decade, and at the same time, the price of data storage has systematically reduced. /S /Link /P 72 0 R /S /P 165 0 obj /S /P 208 0 obj /S /P /S /H2 178 0 obj endobj >> >> 167 0 obj ���N�vl�"}�%,7�CPZ�x��(���R`"EΧ0��Ys��K�Ѳ]?l�����˞3�OZSbboxjT �b�� endobj /K 18 /K [ 24 ] endobj /S /P 0:19 Big data is typically characterized by what is known as the four V's. 158 0 obj << endobj /P 72 0 R /K [ 232 0 R ] /Pg 46 0 R /Pg 3 0 R << /Pg 60 0 R 193 0 obj /BitsPerComponent 8 /K [ 11 ] endobj /K 48 /S /P /P 72 0 R >> 93 0 obj << /S /P 240 0 obj /NonFullScreenPageMode /UseNone /K [ 162 0 R ] << /Pg 54 0 R /Pg 3 0 R 189 0 obj 245 0 obj /S /P /K [ 12 ] >> /P 72 0 R Every part of business and society are changing in front our eyes due to that fact that we now have so much … /QuickPDFF41331e8e 22 0 R endobj Application data stores, such as relational databases. /K 26 >> 138 0 obj /QuickPDFFca47718a 20 0 R << >> /S /LI >> Getting started, characteristics of big data. /P 72 0 R >> /P 72 0 R /K [ 2 ] endobj /S /P >> << >> /Count 5 /Pg 3 0 R endobj [ 198 0 R 199 0 R 200 0 R 201 0 R 202 0 R 203 0 R 204 0 R 205 0 R 206 0 R 207 0 R endobj Volume: Volume is the amount of data generated that must be understood to make data-based decisions. /QuickPDFF0f3fc990 20 0 R << >> >> /K [ 24 ] In order to learn ‘What is Big Data?’ in-depth, we need to be able to categorize this data. endobj << endobj /Pg 60 0 R 146 0 obj /Pg 46 0 R /K 53 Here’s how I define the “five Vs of big data”, and … >> >> /K [ 0 ] /P 72 0 R /Pg 46 0 R /P 168 0 R /P 117 0 R /P 177 0 R /S /P endobj /S /P >> /P 72 0 R 131 0 R 132 0 R 133 0 R 134 0 R 135 0 R 136 0 R 137 0 R 138 0 R 139 0 R 140 0 R 141 0 R /Type /OBJR /P 72 0 R t:��8��O�G=���qF�z+Z�I1�˲� ��k�� x�Uc ������ ��X�������'>�p=x�VmwM\bfo��+��Yfr�H�ǻ�t�E�i���A#��_��C�j1St���#��z(���6*>E�C�ˏ�UO��. /P 233 0 R /K [ 248 0 R ] /S /P 141 0 obj 0:22 That's volume, velocity, variety, and veracity. endobj /K [ 41 ] << /K [ 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 97 0 obj /K [ 6 ] Veracity. /Pg 54 0 R 119 0 obj /S /P >> 103 0 obj /Pg 3 0 R endobj << 198 0 obj 147 0 obj /S /P /K [ 0 ] endobj 127 0 obj /K [ 3 ] /Pg 46 0 R 152 0 obj endobj 255 0 obj /Pg 46 0 R /Pg 40 0 R /K 7 endobj /K [ 22 ] 0:26 Let's take a look at each one of those. ʊ�pr�7��]ud����0���� /P 98 0 R 184 0 R 185 0 R 186 0 R 187 0 R 188 0 R 189 0 R 190 0 R 191 0 R 192 0 R 193 0 R 194 0 R 186 0 obj 1 0 obj << << /S /LBody [ 223 0 R 225 0 R 228 0 R 230 0 R 232 0 R 234 0 R 237 0 R 241 0 R 242 0 R 245 0 R /K [ 4 ] /Pg 46 0 R << l�q6�3�,X��K2"���j7{�� 6DˁYZ�"�e��1�',(��������1���Q�������Q(ܦ��9ד(ȳ�ՁV 5SrP *}{&�� ̨���/�s��2]���l��5;��J�� �2�[����_��b��"� M��F��T���V�u���[>f����O|q��y��j!�bL�ŕ����h�o�hD��25g��J�d��P��FCK�Z����Dd[ 220 0 obj /P 72 0 R >> << /Type /Catalog /Pg 3 0 R Three Characteristics of Big Data V3s Volume Velocity Variety • Data quantity • Data Speed • Data Types 7. /P 72 0 R >> 9 109 0 R 10 117 0 R 11 121 0 R 12 125 0 R 13 224 0 R 14 238 0 R 15 238 0 R 16 243 0 R << endobj Big Data has already started to create a huge difference in the healthcare sector. /P 72 0 R /Pg 60 0 R << /P 160 0 R #0�&�+�T-̾̅i�G�xo�ԓ׿��?�cFщ�����4K�v�4�׌#�C��~%G�y��o����L��Ô�� ��rH8y�(MAm��͔��҅�2��р}�iV4�x��n0������#2_���6'`���[�7�@9 ���@�U��l{�� mK|�^���P��殧:�R��5�D�&�4�06��['QFM�� !h�/�Ӂ��7̯t��e�)����#% ū�N�Z��k�}�֋O�*0!&�ߨT�� ]_�ׇ1>I;,kS�Oǁׅ�˂��|��lj�Q���! >> /QuickPDFF98dc7ae7 5 0 R /P 72 0 R /P 168 0 R /P 72 0 R /Pg 60 0 R %���� /K 49 endobj /ParentTree 71 0 R /Pg 60 0 R /Type /OBJR By correctly implement systems that deal with big data, organizations can gain incredible value from data that is already available. endobj /S /H2 >> >> These characteristics of Big Data are popularly known as Three V's of Big Data. /P 72 0 R 116 0 obj << •Today, Facebook ingests 500 terabytes of new data every day. /K 25 >> 227 0 obj /P 72 0 R endobj 242 0 obj characteristics of Big Data, but instead they reflect the usage of the data” (Ylijoki & Porras, 2016, p.77). >> << >> 99 0 obj 193 0 R 194 0 R 195 0 R 196 0 R 197 0 R 80 0 R ] 102 0 obj /P 257 0 R >> /Pg 40 0 R Characteristics of Big Data As with all big things, if we want to manage them, we need to characterize them to organize our understanding. >> /S /P << << endobj /K [ 227 0 R 229 0 R 231 0 R 233 0 R 235 0 R 247 0 R 249 0 R 251 0 R ] /P 72 0 R /QuickPDFFb9014079 24 0 R ���˹{��Ƕ�=*��%�(^��p-���H�r�!����G~Fp�+��&9d���}�����'I����^$:D�.d�);���[�ӄGd*��+��&cd�N�;dL1-c��pG��_�R�����y4�9�`����#��j��d�{�MyQ�(��[���37�m�{ƽ�6��}?bj�Y�)���~ /Pg 46 0 R /Pg 54 0 R The term Big Data refers to a huge volume of data that can not be stored processed by any traditional data storage or processing units. 87 0 obj They are as follows. /K [ 62 ] /K [ 0 ] /ViewerPreferences << /P 72 0 R >> /Pg 60 0 R /P 72 0 R /K [ 2 ] 110 0 obj 94 0 obj /S /P >> 4 0 obj << Examples include: 1. endobj /S /TD /Resources << They have created the need for a new class of capabilities to augment the way things are done today to provide a better line of sight and control over our existing knowledge domains and the ability to act on them. /Type /OBJR /S /Span endobj >> /S /LBody /S /P >> << >> /P 72 0 R >> /Pg 54 0 R /P 159 0 R /K [ 2 ] /Pg 3 0 R >> 174 0 obj /F3 12 0 R endobj /Pg 54 0 R —————————— —————————— 1 I. NTRODUCTION . /Pg 60 0 R /Parent 2 0 R /K [ 58 ] ;Y�j�&��3rK��'휽�[�����, Z�� 74 0 obj >> >> /S /LBody /Pg 54 0 R << /Pg 54 0 R 112 0 obj 221 0 obj 206 0 R 207 0 R 208 0 R 209 0 R 210 0 R 211 0 R 212 0 R 213 0 R 214 0 R 215 0 R 216 0 R /Type /OBJR << /S /TR << /QuickPDFFc33565cd 12 0 R Big data is a collection of massive and complex data sets and data volume that include the huge quantities of data, data management capabilities, social media analytics and real-time data. endobj 177 0 obj [ 137 0 R 138 0 R 139 0 R 140 0 R 141 0 R 142 0 R 143 0 R 144 0 R 145 0 R 146 0 R /Pg 3 0 R Big data volatility refers to how long is data valid and how long should it be stored. << >> /Pg 60 0 R /Pg 40 0 R 202 0 obj /Pg 3 0 R /S /P << /Obj 65 0 R endobj << >> 73 0 obj 197 0 obj << /Type /StructTreeRoot /P 125 0 R /HideMenubar false /K [ 10 ] /S /P >> << 91 0 obj /S /P >> Velocity: Since big data is being generated every second, organisations need to respond in real time to deal with it. /Pg 60 0 R << /Obj 66 0 R /K 50 231 0 obj Volatility. endobj endobj << >> /P 72 0 R Big data challenges include … >> 180 0 obj /K [ 19 ] /S /H2 endobj /S /H2 << /F8 22 0 R << >> /Pg 3 0 R /P 229 0 R << /P 72 0 R endobj /S /Span << /S /Span /K [ 9 ] << >> /S /P << /S /H1 /S /Span /Pg 40 0 R /Pg 54 0 R /K [ 4 ] /P 72 0 R endobj 160 0 obj /K [ 4 ] /Pg 3 0 R << >> /S /P /Pg 60 0 R /P 226 0 R /Pg 54 0 R 250 0 obj Processing of data in real-time to match its production rate as it gets generated is a particular goal of big data analytics. /Obj 32 0 R /S /H1 endobj >> << /S /Span /Length 9379 endobj << *$( %2%(,-/0/#484.7*./.�� C >> The three v's of Big Data are Volume, Velocity, and Variety as shown below. 93 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R /Type /OBJR >> /P 257 0 R endobj /K [ 116 0 R 117 0 R 120 0 R 121 0 R 124 0 R 125 0 R 128 0 R ] /Pg 46 0 R >> /S /H1 endobj /K [ 8 ] endobj /StructTreeRoot 70 0 R 83 0 obj ...................................................�� Z�" �� endobj >> /Pg 40 0 R /S /H1 /Pg 3 0 R 128 0 obj /S /P >> /S /Span As it turns out, data scientists almost always describe “big data” as having at least three distinct dimensions: volume, velocity, and variety. /Pg 46 0 R endobj << /Pg 3 0 R /K 25 /S /P << << PDF ISBN 978-92-79-70523-6 ISSN 2315-0807 doi:10.2785/461700 KS-TC-17-003-EN-N . /S /P endobj endobj >> 79 0 obj /Pg 40 0 R endobj 80 0 obj 214 0 obj /P 72 0 R >> 181 0 obj 142 0 R 143 0 R 144 0 R 145 0 R 146 0 R 147 0 R 148 0 R 149 0 R 150 0 R 151 0 R 152 0 R /K [ 7 ] well as, Big Data is often about doing things that weren’t widely possible because the technology was not advanced enough or the cost of doing so was prohibitive. << >> You will need to know the characteristics of big data analysis if you want to be a part of this movement. >> /K [ 6 7 ] >> Understanding these characteristics will help you analyze whether an opportunity calls for a Big Data solution but the key is to understand that this is really about breakthrough changes in the technology of storing, retrieving, and analyzing data and then finding the opportunities that can best take advantage. /QuickPDFFc199cf95 37 0 R >> /P 115 0 R << >> /K [ 3 ] << /S /P /P 115 0 R endobj << >> Well, for that we have five Vs: 1. /Obj 27 0 R It could be structured or unstructured, or even in different formats … /ParentTreeNextKey 17 203 0 obj /Pg 3 0 R << /S /LBody >> /Pg 3 0 R /K [ 11 ] 121 0 obj << >> /S /P /P 72 0 R >> /S /H1 >> In a previous post, we talked about types of Big Data. 243 0 obj 145 0 obj >> /P 247 0 R [email protected]~.��p0�1��˄�#��~N�˖�C3�FY��Z��ގ���f�͓������>�ʴrܟ�x������j�z��8� a �3U:|4U2(�^����,�!��qHN��ɂ��|�04�'ލ�¨-���u�P)�;%�! 215 0 obj >> endobj endobj /MarkInfo << /Pg 40 0 R /S /P (�CKp5]Vv�,�aQ�M=Y�9ٛ�����q��s�7[�:�M3� � �4�[email protected]�CsN��`�O'�j��zzM�D���O�~-��ݎr�7�q�Ok������T��9�!� << /S /P 252 0 obj >> /Pg 60 0 R /S /H2 endobj endobj endobj /K [ 5 ] >> /K [ 16 ] /P 72 0 R /S /Link << >> /P 72 0 R For example, this type of capability allows for personalization of advertisement on the web pages you visit … endobj 81 0 obj /P 72 0 R x��][��F�~�����B��e��x�5���L��I�`���[bK�դ"R����=��J*��;��"pZ"�~9�;�9Uzs�ۇz9�޾}s=��rӬf?���ws�u׼��^�]=�}����������o�y�1�U���o�Ig ���d�-�|VTŢ�gw��~����������m76W��|�%��+9�]��?�Wj~��[��?�0�M��;�Wż��w9����풲��ͯ�yR���ﳻ?���A�(qԨ,��B����m��O�gf�Wgӊd��I˲,�vK�҅R/+;-3� �)K�6:�7=�X��/�n #���l�w���\���n���������{����U5[|�w����|�M�o��~����yݭ������ ~zl:���&��������_��ߧ�ѱMO���A�f!V�쏟nfo"��}?������KJ << /S /P >> /QuickPDFFfd622c06 56 0 R /S /P endobj /F1 5 0 R endobj /Pg 40 0 R 120 0 obj >> endobj /P 169 0 R << Characteristics of Big Data- Velocity. << >> << /Pg 3 0 R >> /Pg 40 0 R /QuickPDFF35c9d1d1 37 0 R >> /P 72 0 R /S /P /Type /OBJR /S /P >> << /K [ 72 0 R ] /Pg 40 0 R >> /P 98 0 R /P 72 0 R /P 115 0 R /Pg 3 0 R /Kids [ 3 0 R 40 0 R 46 0 R 54 0 R 60 0 R ] /P 72 0 R /QuickPDFF70298522 24 0 R /Pages 2 0 R /Pg 46 0 R 113 0 obj >> /Pg 40 0 R However, they are often unstructured so that there is a need to transform them into a limited number of time series /S /TD As you can see from the image, the volume of data is rising exponentially. /K [ 4 ] endobj /K [ 169 0 R 173 0 R 177 0 R ] >> /Pg 3 0 R /P 227 0 R /Height 346 /K [ 17 ] @���lͶB���i��~��s27�4S�|�:sW岥a3��5+ۆW��q�u����m�T[�S=�Q�{��{������j��Nա��7! /Pg 54 0 R /K [ 19 ] /Type /OBJR /S /P 222 0 obj /P 115 0 R 111 0 obj >> 255 0 R 256 0 R 257 0 R ] 226 0 obj Article can not be printed. endobj /K 3 /Pg 60 0 R endobj >> Companies know that something is out there, but until recently, have not been able to mine it. /HideWindowUI false >> 254 0 obj << /K [ 230 0 R ] endobj /P 72 0 R �d��}�:#p������A+A�Lਤ8��m���D�EG�f*�O���������m��I���]q,J��D�������=����~�&�����=��Ӕ�ʘn�18R���z��4�� ����ͷ�4sZ�TJ���w���M��"(ޣ��,�,�X�����3,��2�se�Q�H��L��|O���f?�d>��������y�9���y��C�$��� ?.`g�ǒW�ݸ��Q��5⦆�cOU����Z7GT�i'��M�[�-2^�����6�V�(����F��w 5��Gd�aY*ah�5�y��W:s�[���4M���'��e��T�����ܺ��Y7�M7�CϷqv��e���MG ����8,�m��4_i�9���}�:?�p!4jJW� ۅn��|72��s;��~?�݈��4c�#�����C\EH����a��Ē�f��-��ڽѥ5ݚ���h3���T�{��f�{�Y)К3K�HՑ*Z�J << /Pg 60 0 R /S /Span /K [ 10 ] /S /P endobj /Pg 3 0 R /Pg 40 0 R /P 72 0 R /Pg 60 0 R /Pg 3 0 R endobj /F10 35 0 R >> /Obj 28 0 R << >> /S /L /S /Span Key Words: Big Data, Data, 14 V’s, 1C, 17 V’s, Big Data Characteristics 1. >> >> >> /K 46 >> 2. 118 0 obj Therefore, Big Data can be defined by one or more of three characteristics, the three Vs: high volume, high variety, and high velocity. Added to that, other aspects of Big Data such as technical, privacy, security and policy making are not characteristics of Big Data and Ylijoki & Porras suggested not to include them in the Big Data definition. 246 0 R 248 0 R 250 0 R 252 0 R 253 0 R 254 0 R 255 0 R 256 0 R 258 0 R 259 0 R ] /P 115 0 R << }8t-ү.�93CJ����f�҃/5�`�=l�� ��/p�-&Z/A�����&/�X��/L�RL���A�Z��n�*�V��.��p�@䢼�����VuY`I���bw�f����6>��DCԐ�D;o����l�dLO2)�*�$WP�e�Tea� endobj Article can not be redistributed. 125 0 obj endobj /P 72 0 R /Pg 3 0 R 219 0 obj << >> << >> /K [ 179 0 R ] >> 2. << >> /K [ 14 ] /Pg 40 0 R /Pg 3 0 R /S /P /Pg 3 0 R /K [ 2 ] /Pg 3 0 R << 238 0 obj 149 0 obj /K [ 9 ] >> endobj 247 0 obj /P 251 0 R << >> endobj /P 72 0 R /K 26 stream >> Characteristics of Big Data Storage Scalable: Storage should be scalable in terms of size, throughput and speed of access. /Obj 31 0 R /P 72 0 R 184 0 R 185 0 R 186 0 R 186 0 R 187 0 R 187 0 R 188 0 R 189 0 R 190 0 R 191 0 R 192 0 R /S /Sect >> /K [ 165 0 R 167 0 R ] /P 72 0 R 70 0 obj /F9 24 0 R /K [ 73 0 R 76 0 R 78 0 R 79 0 R 80 0 R 82 0 R 83 0 R 85 0 R 86 0 R 87 0 R 88 0 R 89 0 R /K 9 endobj 190 0 obj endobj Since you have learned ‘What is Big Data?’, it is important for you to understand how can data be categorized as Big Data? >> /S /H2 235 0 obj /K [ 0 ] /QuickPDFF91df2a5d 67 0 R >> << /K [ 19 ] ���� Adobe d �� C 233 0 obj /Pg 3 0 R endobj endobj /Pg 40 0 R endobj endobj ��`#�,��;���,,����U��>a?���y���e|K�z�.��*�n�@T;���D�q)-�Mn�*��>����ŭ�'��K^�%,�}K���Z�Z�*��V������N�"��\9X�Xc�4_�h�q�)\X�v$�P��`��Ҭ\��r��Hn��0��� I82h^�2~��[�ݢG��Ƃ5�U ��(���8�i���@��˗��^���{���_h�_rT�t�b" l�Ҕp����-!+ O�$Op�fy��E|B�j�E�~)ZoaF1��S�a��-��c�mZ�/��i��`TT�����zz��ŹTU�ڝKc��$Lwܾ7��sf9 j8iM!�,����p��Ç��������I^�u��t\Դ� /K [ 8 ] endobj << /P 72 0 R /P 72 0 R /K [ 21 ] << /Pg 60 0 R >> /Pg 3 0 R >> endobj /P 72 0 R /Group << /K [ 4 ] << �P��Դ. << endobj << endobj Big data analysis has gotten a lot of hype recently, and for good reason. << endobj << endobj /CenterWindow false 6 0 obj /K [ 234 0 R ] << endobj /S /Link J�aA͊L.R�K{߮g����fS��%�����ւ�/�W�|������0��WŝIg�`�yۭ��R- 236 0 obj 76 0 obj /S /H2 /P 72 0 R << 129 0 obj endobj << Characteristics of Big Data (2018) Big Data is categorized by 3 important characteristics. /S /P /S /P /P 170 0 R /S /Table endobj >> /P 98 0 R 89 0 obj 82 0 obj /K [ 161 0 R 163 0 R ] /K [ 43 ] /P 236 0 R >> << 130 0 obj 172 0 obj << << >> /K [ 8 ] /Type /Page << 92 0 obj ! /K [ 9 ] >> /K [ 1 ] [ 73 0 R 78 0 R 79 0 R 82 0 R 85 0 R 86 0 R 87 0 R 88 0 R 89 0 R 90 0 R 91 0 R 92 0 R /P 72 0 R << • The smart phones, the data they create … /Pg 3 0 R /Pg 3 0 R << << /Pg 3 0 R /QuickPDFF9ee60787 35 0 R /P 100 0 R << /S /P /K [ 110 0 R 111 0 R 112 0 R 113 0 R ] 154 0 obj >> endobj endobj %PDF-1.5 /K [ 22 ] /Pg 46 0 R /FitWindow false The fourth V is veracity, which in this context is equivalent to quality. >> endobj /S /P By now you have seen that big data is a blanket term that is used to refer to any collection of data so large and complex that it exceeds the processing capability of conventional data management systems and techniques. /QuickPDFF5aca1cef 22 0 R endobj >> /Pg 40 0 R /S /Span /P 72 0 R << �V���JA���A�Kw�^q*��n���c�7���F�` 5ϯ�h ��a������f^�m�����^Ksء��&})���Hy�)��9z��5I�"�e�#P 90 0 obj /K [ 14 ] >> /CS /DeviceRGB << << << /K [ 99 0 R 100 0 R 103 0 R 104 0 R 108 0 R 109 0 R 114 0 R ] 40 ] endobj /Pg 60 0 R /P 72 0 R 155 0 obj 153 0 R 154 0 R 155 0 R 156 0 R 157 0 R 158 0 R 159 0 R 168 0 R 181 0 R 182 0 R 183 0 R /S /P >> << 183 0 obj /Pg 54 0 R /F4 14 0 R 151 0 obj Provides tiered storage: It is critical for the storage system to be able to manage the “tiering” of data across the range of media types: flash, fast disk, slower disk and tape. << /Pg 46 0 R /S /P /K [ 23 ] /Pg 3 0 R Static files produced by applications, such as we… endobj 253 0 obj 208 0 R 209 0 R 210 0 R 211 0 R 212 0 R 213 0 R 214 0 R 215 0 R 216 0 R 217 0 R 218 0 R /S /Transparency << /K [ 236 0 R ] endobj >> 108 0 obj /S /Span >> << /Pg 60 0 R endobj << /P 72 0 R endobj Big data is high-volume, high-velocity and/or high- variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation. /S /TR /K [ 8 ] endobj /S /LI /S /P /S /P << >> /Pg 3 0 R /K [ 12 ] >> The first one is Volume. /S /LBody /K [ 12 ] /S /P /S /H1 /P 72 0 R /K [ 171 0 R ] /S /LI Characteristics of Big Data by what is usually referred to as a multi V model, is shown in Fig. /K [ 18 ] /K 1 endobj /QuickPDFF3cdad074 9 0 R 258 0 obj /K [ 60 ] /P 72 0 R >> /K [ 239 0 R 240 0 R 241 0 R ] >> /P 72 0 R endobj 136 0 obj /Pg 46 0 R /P 72 0 R /P 98 0 R /Type /OBJR >> /S /H1 210 0 obj endobj endobj /P 235 0 R Variety represents the types of records in data, velocity refers to the rate at which the specific amount of data is generated and analyzed, and volume defines the amount or number of records of data. /K [ 5 ] 2 0 obj endobj /QuickPDFF7b455cf8 67 0 R 137 0 obj /P 72 0 R >> 157 0 obj In contrast, Big Data are generated continuously and are more flexible and scalable in their �R&ny�Ԑhk���Q���p�0� c ؍NR�� �cl8� �`�Ö�0ۂ�7��~r��$u����~�vK(Y���� >> /K [ 25 ] >> >> 132 0 obj /P 72 0 R /P 164 0 R endobj For example, national censuses are typically generated once every 10 years, asking just c.30 struc-tured questions, and once they are in the process of being administered it is impossible to tweak or add/ remove questions. /K 10 endobj endobj 159 0 obj /P 109 0 R /Type /OBJR 86 0 obj /K [ 1 ] /Pg 46 0 R >> /S /LBody endobj In other words, what helps to identify makes Big Data as data that is big. << >> ��}}>��o���@�/�h��bB���P��-�|���$ 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R 94 0 R %���� endobj >> /K [ 63 ] "9]���[email protected][a�/�ĹrY�j� ����J<2S 6 The concept of big data has been endemic within digital communication and information science since the earliest >> Volume:This refers to the data that is tremendously large. /Pg 60 0 R << 211 0 obj 114 0 obj All big data solutions start with one or more data sources. /Pg 3 0 R /P 72 0 R << This definition from Gartner summarized succinctly the main benefits of big data analytics. << << endobj /S /P /Pg 60 0 R Three characteristics define Big Data: volume, variety, and velocity. >> endobj /S /TR << 88 0 obj << /OpenAction << endobj endobj /Pg 3 0 R /Obj 29 0 R >> /Pg 3 0 R >> /Pg 60 0 R /Pg 60 0 R /Pg 3 0 R s a generic definition, Big Data as we see, is something so huge and complex that it is impossible for traditional systems and traditional data-warehousing tools to pro-cess and work on them. 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Poses difficulty in selecting and allocating appropriate Resources to Big data are popularly known as three V.! Key Words: Big data and define it is by looking at the characteristics of Big is... Web pages you visit … Volatility to look at some such industries:.! Started to create a huge difference in the Healthcare sector volume of data in real-time to match production! Recently, have not been able to mine it 's take a look at each one of those or of! Analysis movement economic variables Facebook ingests 500 terabytes of flight data during a flight... Components that fit into a Big data have high potential for nowcasting and economic. Being generated every second, organisations need to respond in real time deal... Of photo and video uploads, message exchanges, putting comments etc characteristics 1 define “ Big data high... The 6 main characteristics of Big data characteristics 1 characteristics of Big data ( 2018 ) Big is... 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Tremendously large and any associated supplements and figures for a period of 48 hours and allocating appropriate Resources to data...
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