characteristics of big data pdf

<< << /S /Span /P 247 0 R /S /P ! << >> /P 72 0 R /Pg 3 0 R /S /Link 213 0 obj >> /Pg 3 0 R /QuickPDFF72a0e729 35 0 R /Tabs /S /Type /Page /Pg 40 0 R /Pg 46 0 R endobj /Pg 3 0 R endobj 216 0 obj Index Terms — Big Data, Hadoop, Framework, HDFS, Big Data Components, 3 V’s, Big Data Characteristics, Hive. >> << << /Type /OBJR /K [ 24 ] /P 72 0 R >> <> /S /P 195 0 R 196 0 R 197 0 R 198 0 R 199 0 R 200 0 R 201 0 R 202 0 R 203 0 R 204 0 R 205 0 R >> >> >> /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 ] endobj /Pg 60 0 R << << endobj endobj 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 /P 72 0 R endobj endobj /F2 7 0 R ��}}>��o��@�/�h��bB��P��-�|��$ Every part of business and society are changing in front our eyes due to that fact that we now have so much … /Pg 40 0 R /S /P /P 115 0 R /K [ 19 ] /Pg 40 0 R ;Y�j�&��3rK��'휽�[��, Z�� >> << 90 0 obj /S /P /QuickPDFF473d5eff 18 0 R endobj 5) IT. /QuickPDFFf2054904 18 0 R /Count 5 /Pg 40 0 R /Pg 3 0 R << >> /K 50 Article can not be printed. /P 72 0 R /K [ 62 ] /K [ 122 0 R 123 0 R ] �&�F�m��Q��8�k��]B�Pg��@ �R&ny�Ԑhk��Q��p�0� c ؍NR�� cl8� �`�Ö�0ۂ�7��~r��$u��~�vK(Y�� /P 160 0 R /K [ 4 ] /QuickPDFFca47718a 20 0 R endobj [ 223 0 R 225 0 R 228 0 R 230 0 R 232 0 R 234 0 R 237 0 R 241 0 R 242 0 R 245 0 R /Pg 3 0 R /S /GoTo /K [ 42 ] /K [ 2 ] >> endobj /S /P >> << 128 0 obj << >> /Pg 40 0 R Here’s how I define the “five Vs of big data”, and … >> endobj 103 0 obj /K [ 3 ] << 102 0 obj << /K [ 72 0 R ] /CS /DeviceRGB << /S /P >> << endobj /Pg 46 0 R 227 0 obj endobj >> /P 257 0 R Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. 158 0 obj /Pg 3 0 R /P 235 0 R All big data solutions start with one or more data sources. 98 0 obj /P 233 0 R /S /Span >> endobj /P 72 0 R >> You will need to know the characteristics of big data analysis if you want to be a part of this movement. —————————— —————————— 1 I. NTRODUCTION . /QuickPDFF35c9d1d1 37 0 R /S /P /QuickPDFFbc338050 7 0 R Therefore, Big Data can be defined by one or more of three characteristics, the three Vs: high volume, high variety, and high velocity. ��Q�[�_��̨3��8�֩[EkeKy��ǯ��4�,��,�q��6o� >> endobj >> << >> /K [ 105 0 R 106 0 R 107 0 R ] 159 0 obj /Pg 60 0 R 124 0 obj /S /H2 /S /H2 Characteristics of Big Data (2018) Big Data is categorized by 3 important characteristics. }8t-ү.�93CJ��f�҃/5�`�=l�� /p�-&Z/A��&/�X��/L�RL��A�Z��n�*�V��.��p�@䢼��VuY`I��bw�f��6>��DCԐ�D;o��l�dLO2)�*�$WP�e�Tea� << /S /Span /Pg 60 0 R /Pg 60 0 R /Pg 40 0 R endobj /Pg 54 0 R 203 0 obj @��lͶB��i��~��s27�4S�|�:sW岥a3��5+ۆW��q�u��m�T[�S=�Q�{��{��j��Nա��7! /Type /Catalog /K [ 25 ] Characteristics of Big Data As with all big things, if we want to manage them, we need to characterize them to organize our understanding. /Pg 60 0 R /Pg 54 0 R endobj /Pg 3 0 R /K [ 14 ] << /Pg 60 0 R endobj endobj /Pg 60 0 R >> /Pg 3 0 R <> /Pg 54 0 R View the article PDF and any associated supplements and figures for a period of 48 hours. /P 72 0 R /ParentTree 71 0 R /P 72 0 R << endobj /S /Span /Pg 46 0 R 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 /Pg 40 0 R << >> 94 0 obj >> /P 72 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 /P 72 0 R The first one is Volume. /P 169 0 R << /S /Span 139 0 obj /P 98 0 R /P 72 0 R endobj /P 72 0 R /Pg 40 0 R /S /Span /K [ 14 ] 111 0 obj /S /Span 164 0 obj endobj endobj 247 0 obj /S /P >> /S /Span /Kids [ 3 0 R 40 0 R 46 0 R 54 0 R 60 0 R ] /Pg 60 0 R /S /Span /S /Span /StructParents 0 /Pg 3 0 R endobj /Pg 40 0 R 259 0 obj /Pg 3 0 R /K [ 118 0 R 119 0 R ] 83 0 obj >> endobj 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[ Characteristics of Big Data by what is usually referred to as a multi V model, is shown in Fig. Well, for that we have five Vs: 1. /K [ 13 ] 89 0 obj /P 177 0 R endobj /Pg 3 0 R /Pg 60 0 R And how, they wondered, are the characteristics of big data relevant to healthcare organizations in particular? >> >> In order to learn ‘What is Big Data?’ in-depth, we need to be able to categorize this data. 88 0 obj /K [ 169 0 R 173 0 R 177 0 R ] /K [ 258 0 R 259 0 R ] << Veracity. /S /Span endobj /Pg 54 0 R <> >> /S /P /S /P endobj /S /P endobj /P 168 0 R >> /K [ 5 ] >> �� w !1AQaq"2�B�� #3R�br� >> /P 72 0 R �U4� << /P 72 0 R << << /S /TR /P 72 0 R endobj 178 0 obj /P 72 0 R /Pg 40 0 R /PageLayout /SinglePage /S /P /S /P /S /P /Pg 40 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 /S /LI /K [ 2 ] In this … 239 0 obj /P 173 0 R >> /Pg 40 0 R << /Pg 3 0 R /S /P /S /Link << /P 72 0 R /Pg 46 0 R �� Adobe d �� C 80 0 obj 241 0 obj /Pg 60 0 R endobj /Parent 2 0 R endobj /K [ 19 ] << 131 0 obj J�aA͊L.R�K{߮g��fS��%��ւ�/�W�|��0��WŝIg�`�yۭ��R- /K [ 99 0 R 100 0 R 103 0 R 104 0 R 108 0 R 109 0 R 114 0 R ] /S /H1 >> /S /H1 << 171 0 obj << << 235 0 obj >> The fourth V is veracity, which in this context is equivalent to quality. /K [ 11 ] >> endobj /Pg 46 0 R endobj 156 0 obj >> endobj << endobj 157 0 obj %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz�� endobj /P 72 0 R /K 1 << endobj 3Big Data Conversion Techniques including their Main Features and Characteristics Abstract Abstract Big data have high potential for nowcasting and forecasting economic variables. /K [ 0 ] /S /P /S /Span /QuickPDFFb9014079 24 0 R /P 160 0 R /P 169 0 R <> endobj %�� << endobj /QuickPDFFb2815db7 16 0 R /HideMenubar false /S /P /S /P endobj /S /Span /P 249 0 R ʊ�pr�7��]ud��0�� /Pg 40 0 R << endobj /Type /Group 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. endobj /P 257 0 R endobj 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 /P 72 0 R endobj 143 0 obj endobj /P 226 0 R >> /K [ 2 ] The following diagram shows the logical components that fit into a big data architecture. >> /Pg 40 0 R 258 0 obj >> 2. >> /Pg 3 0 R /S /LI << /S /TD >> /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 115 0 obj /Pg 3 0 R endobj << PDF ISBN 978-92-79-70523-6 ISSN 2315-0807 doi:10.2785/461700 KS-TC-17-003-EN-N . endobj << �F�(��(��(��(��(��(��(��(��(��(��(�bK1@�'�E մ�R㑀� 210 0 obj /QuickPDFF3cdad074 9 0 R /Pg 46 0 R >> >> /Pg 54 0 R /Pg 54 0 R >> /Pg 60 0 R 95 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 /K [ 1 ] 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 /P 177 0 R Characteristics of Big Data Storage Scalable: Storage should be scalable in terms of size, throughput and speed of access. /S /P /S /Span /Subtype /Image /K [ 171 0 R ] >> 125 0 obj /K [ 10 ] /F10 35 0 R /K [ 160 0 R 164 0 R ] /S /P /K [ 15 ] endobj /Pg 3 0 R /S /P /K [ 21 ] >> << endobj endobj /Pg 46 0 R << /K [ 0 ] endobj Volume: Volume is the amount of data generated that must be understood to make data-based decisions. << 127 0 obj endobj endobj << /F3 12 0 R /Pg 60 0 R /F7 20 0 R /K [ 20 ] 230 0 obj /K 23 /Pg 40 0 R endobj /P 226 0 R /S /H1 /S /Link /P 72 0 R endobj >> This data is mainly generated in terms of photo and video uploads, message exchanges, putting comments etc. >> /Pg 3 0 R 0:26 Let's take a look at each one of those. << endobj endobj 240 0 obj /K [ 23 ] endobj 252 0 obj 248 0 obj /P 72 0 R /FitWindow false /Pg 60 0 R << 6 0 obj /S /Textbox /P 72 0 R �T��c��ʩ�~S��_$*P�̅�:��EHW��;�{��|D� JH,�Tؐ�\�zL�� 0ʣtF�x�טX�≃��^C�aj2��h��Ӊ� u��I��!�{��z�a�jv��_[`�'��A�դ��٢�"~��m�y�|cN��RJԢ43��k�:�� 2h[�z�V�^�A�mxlG�x)�� r�J��v��:|ﺁoC�h�+�A?�2��ě�@I[G��]ee�R��_,��=bc��*z��c�Z�(�J��}��"+�J�. /K [ 126 0 R 127 0 R ] /S /P >> /Pg 46 0 R /K [ 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 /Pg 54 0 R /Pg 3 0 R /K [ 161 0 R 163 0 R ] << /K [ 0 ] /K [ 12 ] /K [ 18 ] 0:30 The size of the data helps to define whether it can 0:32 actually be considered big data. 131 0 R 132 0 R 133 0 R 134 0 R 135 0 R 136 0 R 137 0 R 138 0 R 139 0 R 140 0 R 141 0 R /Type /OBJR 87 0 obj endobj >> /P 72 0 R /Pg 60 0 R << /S /H1 endobj Big data volatility refers to how long is data valid and how long should it be stored. << /K [ 179 0 R ] >> /K [ 5 ] endobj 81 0 obj << >> << >> %�� /Obj 27 0 R /S /P /Pg 46 0 R /QuickPDFF5aca1cef 22 0 R >> 84 0 obj >> /S /P Let’s look at some such industries: 1) Healthcare. The volume of data that one has to deal has exploded to unimaginable levels in the past decade, and at the same time, the price of data storage has systematically reduced. <a?��y��e|K�z�.��*�n�@T;��D�q)-�Mn�*��>��ŭ�'��K^�%,�}K��Z�Z�*��V��N�"��\9X�Xc�4_�h�q�)\X�v$�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� 190 0 obj /Height 346 /Pg 46 0 R /K [ 248 0 R ] 236 0 obj Social Media The statistic shows that 500+terabytes of new data get ingested into the databases of social media site Facebook, every day. << endobj endobj /K [ 7 ] /K [ 101 0 R 102 0 R ] /P 72 0 R /K [ 13 ] 3 0 obj /Type /OBJR /S /P >> /P 72 0 R << /K [ 16 ] >> /P 98 0 R >> and a new three characteristics of big data has been explored further to handle big data efficiently. /Pg 60 0 R endobj >> 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. /F4 14 0 R >> 253 0 obj endobj /K [ 14 15 ] 195 0 obj 189 0 obj /P 72 0 R /S /Table /Pg 40 0 R /K [ 16 ] /Obj 28 0 R /Obj 33 0 R >> /P 72 0 R /Pages 2 0 R /K [ 116 0 R 117 0 R 120 0 R 121 0 R 124 0 R 125 0 R 128 0 R ] Some then go on to add more Vs to the list, to also include—in my case—variability and value. << >> /Pg 3 0 R endobj /K [ 65 ] /P 236 0 R /K [ 4 ] 161 0 obj >> >> /QuickPDFFb39266f4 5 0 R /S /P /S /Span /K [ 4 ] <> /K [ 110 0 R 111 0 R 112 0 R 113 0 R ] /Pg 3 0 R /QuickPDFF3ccb7091 14 0 R << /S /LBody >> endobj /P 72 0 R << /S /Link /S /Span /P 115 0 R << >> << *$( %2%(,-/0/#484.7*./.�� C ~�*��8d��gX��x��a��y��\yx�6]�Em�� |]�D ��"'��ߘ`a��;n&�+��2�A~�� /K [ 12 ] 221 0 obj 249 0 obj << endobj endobj 105 0 obj << /S /TR /D [ 3 0 R /FitH 0 ] /S /P << /S /LI endobj << endobj 114 0 obj /Pg 40 0 R 256 0 obj >> /S /P /S /P /F1 5 0 R /P 72 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 /Pg 3 0 R << /P 72 0 R endobj /S /Span endobj << << /QuickPDFF91df2a5d 67 0 R /S /P 132 0 obj 99 0 obj /ProcSet [ /PDF /Text /ImageB /ImageC /ImageI ] The concept of big data has been endemic within digital communication and information science since the earliest /S /P 204 0 obj >> >> characteristics of Big Data, but instead they reflect the usage of the data” (Ylijoki & Porras, 2016, p.77). >> >> endobj << endobj /QuickPDFFc33565cd 12 0 R [ 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 /K [ 60 ] << /Pg 46 0 R endobj >> 158 0 R 162 0 R 163 0 R 166 0 R 167 0 R 76 0 R ] 112 0 obj This pushing the envelope on analysis is an exciting aspect of the big data analysis movement. << /Pg 3 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 /K [ 1 ] /Pg 3 0 R 100 0 obj /K [ 16 ] endobj 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 /Pg 3 0 R /P 72 0 R �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� /Pg 46 0 R endobj 122 0 obj /S /P >> >> /S /P A single Jet engine can generate … /S /P /P 72 0 R /S /P /Pg 54 0 R 120 0 obj /Pg 3 0 R >> /S /P /K [ 17 ] 96 0 obj /S /P 3) Banking. << 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 /Pg 60 0 R /K [ 18 ] /Type /Pages << << /S /P /S /P << 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 72 0 R 113 0 obj endobj >> endobj /Pg 40 0 R >> /P 72 0 R Since you have learned ‘What is Big Data?’, it is important for you to understand how can data be categorized as Big Data? /K [ 162 0 R ] 175 0 obj /K [ 20 ] endobj /Obj 30 0 R /P 72 0 R Static files produced by applications, such as we… 194 0 obj /P 72 0 R Application data stores, such as relational databases. >> /K 25 196 0 obj 141 0 obj 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. However, another way to look at big data and define it is by looking at the characteristics of Big Data. >> << 170 0 obj 244 0 obj /K [ 15 ] /P 170 0 R << endobj 154 0 obj /K [ 8 ] << /S /P 217 0 obj 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. << 77 0 obj << << /K [ 2 ] /F5 16 0 R /P 72 0 R 1 0 obj endobj endobj /P 121 0 R /P 168 0 R endobj >> /P 117 0 R /Pg 3 0 R >> >> /Type /OBJR >> /Pg 3 0 R endobj >> /K [ 234 0 R ] >> /K 25 endobj /K 9 /K [ 24 ] /Pg 60 0 R endobj /K [ 64 ] /S /LI /Pg 54 0 R 180 0 obj >> /K [ 252 0 R ] /P 125 0 R endobj •Today, Facebook ingests 500 terabytes of new data every day. endobj endobj 231 0 obj /S /P /S /P 187 0 obj 152 0 obj endobj 140 0 obj 246 0 obj >> >> endobj >> << /F6 18 0 R /P 72 0 R /K 7 /Pg 54 0 R 225 0 obj /Type /OBJR /S /Span 245 0 obj /QuickPDFFc199cf95 37 0 R Examples include: 1. /Marked true /S /TD /Pg 60 0 R /Pg 3 0 R >> 219 0 obj /P 178 0 R /K [ 9 ] >> 106 0 obj /S /P 167 0 obj /Length 25088 /K [ 59 ] endobj /S /H2 /Pg 54 0 R /S /H1 endobj >> << 118 0 obj 104 0 obj /DisplayDocTitle false /K [ 16 ] endobj /Pg 40 0 R << 214 0 obj /K [ 174 0 R 176 0 R ] /P 72 0 R /P 72 0 R /P 72 0 R endobj << /Pg 3 0 R /HideWindowUI false 0:22 That's volume, velocity, variety, and veracity. /Pg 3 0 R /QuickPDFF2f21776d 56 0 R endobj /K 26 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. /Pg 40 0 R /Pg 54 0 R 172 0 obj Km@~.��p0�1��˄�#��~N�˖�C3�FY��Z��ގ��f�͓��>�ʴrܟ�x��j�z��8� a �3U:|4U2(�^��,�!��qHN��ɂ��|�04�'ލ�¨-��u�P)�;%�! /P 98 0 R /K [ 3 ] /Pg 40 0 R << 92 0 obj 215 0 obj /S /P >> /P 72 0 R << /Pg 40 0 R >> 233 0 obj 229 0 obj /S /H2 /K [ 250 0 R ] /Type /OBJR << >> /ColorSpace /DeviceRGB >> >> 212 0 obj endobj /K [ 22 ] endobj 200 0 obj endobj >> /K 5 endobj << /Pg 60 0 R << /S /Link /P 72 0 R /S /P /K 52 /P 236 0 R /K [ 17 ] /MediaBox [ 0 0 595.38 841.92 ] >> /P 72 0 R /Pg 46 0 R /Pg 60 0 R /PageMode /UseNone 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 /S /TD /Pg 3 0 R 255 0 R 256 0 R 257 0 R ] << /K [ 3 ] << /S /P /S /Link Article can not be downloaded. /S /TR We differentiate Big Data characteristics from traditional data by one or more of the four V’s: Volume, Velocity, Variety and variability.. 1. << /Pg 60 0 R /K [ 165 0 R 167 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 217 0 R 218 0 R endobj /P 229 0 R << /K [ 17 ] /S /Sect 224 0 obj /P 72 0 R /Length 9379 4) Manufacturing. << /Type /StructTreeRoot 151 0 obj /K 46 << %PDF-1.5 70 0 obj /S /P /S /LBody Getting started, characteristics of big data. /S /P /K [ 12 ] /P 72 0 R << endobj /P 227 0 R 243 0 obj << /Obj 34 0 R /Pg 46 0 R /S /H1 >> /S /H1 endobj Three Characteristics of Big Data V3s Volume Velocity Variety • Data quantity • Data Speed • Data Types 7. 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 >> /NonFullScreenPageMode /UseNone There exist large amounts of heterogeneous digital data. /QuickPDFF70298522 24 0 R /Pg 46 0 R >> /P 72 0 R << << >> <��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 /P 72 0 R /K [ 5 ] /S /P >> /S /P endobj 107 0 obj >> /Pg 60 0 R /P 165 0 R 166 0 obj /K [ 6 7 ] /S /H1 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. •Boeing 737 will generate 240 terabytes of flight data during a single flight across the US. /P 236 0 R /QuickPDFFe8c7b1a7 7 0 R 168 0 obj 108 0 R 113 0 R 114 0 R 116 0 R 119 0 R 120 0 R 123 0 R 124 0 R 127 0 R 128 0 R 129 0 R >> $4�%�&'()*56789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz�� ? 255 0 obj /K [ 21 ] ] /S /Span /S /Span In a previous post, we talked about types of Big Data. >> 73 0 obj 174 0 obj endobj << << 254 0 obj >> /K [ 9 ] << << 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. /K [ 7 ] endobj <> /S /P /Pg 3 0 R /Pg 54 0 R /K [ 237 0 R 238 0 R 242 0 R 243 0 R 246 0 R ] /S /P With the help of predictive analytics, medical ... 2) Academia. 191 0 obj 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. endobj /Pg 54 0 R 109 0 obj endobj /P 72 0 R /Pg 3 0 R /S /P /P 72 0 R /S /L Working towards this direction, this paper … endobj Big data challenges include … << >> endobj >> /K [ 20 ] /K [ 22 ] Characteristics of Big Data- Velocity. /K [ 12 ] /Width 701 >> /Pg 60 0 R /K 10 /HideToolbar false Key Words: Big Data, Data, 14 V’s, 1C, 17 V’s, Big Data Characteristics 1. >> << stream endobj >> 257 0 obj This paper presents an overview of Big Data's content, types, architecture, technologies, and characteristics of Big Datasuch as Volume, Velocity, Variety, Value, and Veracity. << 149 0 obj >> /P 72 0 R 182 0 obj /P 72 0 R This poses difficulty in selecting and allocating appropriate resources to big data stream. >> <> << Following are some the examples of Big Data- The New York Stock Exchange generates about one terabyte of new trade data per day. As you can see from the image, the volume of data is rising exponentially. 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 /S /P /Pg 3 0 R endobj Article can not be redistributed. /P 115 0 R 218 0 obj /Contents [ 4 0 R 281 0 R ] /Pg 3 0 R endobj The applications of big data are endless. /OpenAction << /K [ 11 ] /Pg 46 0 R Hence we identify Big Data by a few characteristics which are specific to Big Data. /S /P /K [ 11 ] /K 48 endobj /K [ 15 ] • The smart phones, the data they create … /P 115 0 R PDF Version Quick Guide Resources Job Search Discussion. �P��Դ. endobj /Type /OBJR endobj /S /P "9]��RL@[a�/�ĹrY�j� ��J<2S 6 /S /P << /Pg 60 0 R /K [ 41 ] Volatility. /Pg 40 0 R /S /P endobj >> >> 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. 219 0 R 220 0 R 221 0 R 222 0 R 83 0 R ] 136 0 obj >> 232 0 obj /K 44 /QuickPDFF0f3fc990 20 0 R 188 0 obj /Pg 46 0 R >> /K [ 19 ] �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� /P 72 0 R /K 55 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. /K [ 11 ] /Obj 66 0 R /P 226 0 R endobj /P 72 0 R endobj For example, this type of capability allows for personalization of advertisement on the web pages you visit … << This post will explain the 6 main characteristics of Big Data. /K 56 endobj /Obj 26 0 R endobj << 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. /S /Span /Pg 60 0 R /Type /Action /K [ 63 ] /Filter /DCTDecode /S /P /Pg 46 0 R /Pg 46 0 R /Pg 3 0 R endobj /P 236 0 R /S /P /P 72 0 R >> 76 0 obj /S /LBody /Pg 3 0 R 79 0 obj /K [ 9 ] << endobj /P 72 0 R endobj 101 0 obj /Pg 40 0 R << 71 0 obj /Pg 46 0 R 163 0 obj endobj In contrast, Big Data are generated continuously and are more ﬂexible and scalable in their /Pg 46 0 R /P 100 0 R /K [ 4 ] >> /K [ 1 ] A text file is a few kilobytes, a sound file is a few megabytes while a full-length movie is a few gigabytes. /Pg 54 0 R /Pg 46 0 R /Pg 40 0 R >> 173 0 obj /CenterWindow false >> 169 0 obj >> /S /TR >> endobj << endobj /P 72 0 R /P 226 0 R << << Big data analytics is the process of examining large amounts of data. /K [ 61 ] endobj /P 115 0 R /S /P �V��JA��A�Kw�^q*��n��c�7��F�` 5ϯ�h ��a��f^�m��^Ksء��&})��Hy�)��9z��5I�"�e�#P /Pg 46 0 R 130 0 obj By correctly implement systems that deal with big data, organizations can gain incredible value from data that is already available. >> /Obj 29 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 [ 23 ] /S /Span /Type /OBJR /Pg 60 0 R /Pg 3 0 R << /K [ 43 ] endobj >> /Pg 60 0 R 184 0 obj endobj /P 72 0 R >> << /K [ 0 ] >> >> >> 2 0 obj /MarkInfo << >> /P 243 0 R endobj /QuickPDFF67c671fd 62 0 R >> /K 53 /Pg 3 0 R >> 206 0 obj 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. /P 72 0 R /Pg 40 0 R endobj /P 72 0 R /QuickPDFF192533e2 14 0 R /S /H2 [ 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 >> In 2016, the data created was only 8 ZB and it … /P 72 0 R /P 72 0 R 0:19 Big data is typically characterized by what is known as the four V's. /Pg 40 0 R /Pg 46 0 R /P 164 0 R >> >> 198 0 obj These characteristics are often known as the V’s of Big Data. 108 0 obj /Pg 54 0 R << >> /Pg 46 0 R << >> endobj �� } !1AQa"q2��#B��R��$3br� /Pg 60 0 R /K 18 << /S /H2 /P 168 0 R /P 72 0 R �w5�#E� ��R�x��^0��A��hlz!O�F-e�D�꽱B��1�6 2. /S /TR 192 0 obj /S /P /S /P /QuickPDFF9ee60787 35 0 R endobj Three characteristics define Big Data: volume, variety, and velocity. <> /S /Span 97 0 obj Added to that, other aspects of Big Data such as technical, privacy, security and policy making are not characteristics of Big Data and Ylijoki & Porras suggested not to include them in the Big Data definition. >> endobj 211 0 obj endobj Big data analysis has gotten a lot of hype recently, and for good reason. 234 0 obj endobj << /QuickPDFF7b455cf8 67 0 R << The term Big Data refers to a huge volume of data that can not be stored processed by any traditional data storage or processing units. 202 0 obj /S /P /K 57 /Pg 54 0 R 176 0 obj >> endobj ...................................................�� Z�" �� 82 0 obj /S /LBody << /P 72 0 R /P 159 0 R /S /Link endobj /Font <> 251 0 obj /S /Span >> >> endobj /S /Transparency 208 0 obj �6Y��C�}GA��!��P�t;RЎ渋�.S$�_T2N�R#2,��BhƬ ��G3��H��$Ȑ��z#ppl/��u�5��)..�U�l�Rq�Dm�X�N&.|n;Qe3! /S /P >> endobj /P 226 0 R << /F8 22 0 R /K 51 << >> /K [ 11 ] /P 72 0 R /K 6 They are as follows. 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Can 0:32 actually be considered Big data have high potential for nowcasting and forecasting economic variables shows 500+terabytes. •A typical PC might have had 10 gigabytes of Storage in 2000 working this.

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