{"id":716,"date":"2021-09-08T13:56:21","date_gmt":"2021-09-08T13:56:21","guid":{"rendered":"https:\/\/esi.ac.ma\/formation\/formation-continue\/formation-a-la-carte\/big-data-data-analysis\/"},"modified":"2021-09-08T13:56:21","modified_gmt":"2021-09-08T13:56:21","slug":"big-data-data-analysis","status":"publish","type":"page","link":"https:\/\/esi.ac.ma\/en\/formation\/formation-continue\/big-data-data-analysis\/","title":{"rendered":"Big Data &#038; Data Analysis"},"content":{"rendered":"<p>[vc_row][vc_column][vc_custom_heading text=&#8221;Objectifs&#8221; google_fonts=&#8221;font_family:Montserrat%3Aregular%2C700|font_style:700%20bold%20regular%3A700%3Anormal&#8221;][vc_column_text]<\/p>\n<ul>\n<li>Comprendre les origines et les d\u00e9fis du traitement des donn\u00e9es massives.<\/li>\n<li>\u00c9tudier les fondements de l\u2019architecture HADOOP et de MapReduce.<\/li>\n<li>Maitriser le concept des bases de donn\u00e9es NoSQL.<\/li>\n<li>Introduire les algorithmes du Big Data Analytics.<\/li>\n<\/ul>\n<p>[\/vc_column_text][vc_custom_heading text=&#8221;Contenu&#8221; google_fonts=&#8221;font_family:Montserrat%3Aregular%2C700|font_style:700%20bold%20regular%3A700%3Anormal&#8221;][vc_row_inner][vc_column_inner width=&#8221;1\/3&#8243;][vc_custom_heading text=&#8221;Introduction au Big Data&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; google_fonts=&#8221;font_family:Montserrat%3Aregular%2C700|font_style:700%20bold%20regular%3A700%3Anormal&#8221;][vc_column_text]<\/p>\n<ul>\n<li>Origines et D\u00e9finitions<\/li>\n<li>Enjeux du Big Data<\/li>\n<li>Architecture Big Data<\/li>\n<\/ul>\n<p>[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/3&#8243;][vc_custom_heading text=&#8221;Analyse des Big Data&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; google_fonts=&#8221;font_family:Montserrat%3Aregular%2C700|font_style:700%20bold%20regular%3A700%3Anormal&#8221;][vc_column_text]<\/p>\n<ul>\n<li>Moteur de traitement SPARK<\/li>\n<li>Pr\u00e9paration des donn\u00e9es (PreProcessing, Feature Selection)<\/li>\n<li>Analyse des donn\u00e9es (Regression, Clustering, \u2026)<\/li>\n<li>Indexation et recherche de donn\u00e9es (Elasticsearch, Kibana)<\/li>\n<li>Visualisation des donn\u00e9es (DataViz)<\/li>\n<\/ul>\n<p>[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/3&#8243;][vc_custom_heading text=&#8221;Ecosyst\u00e8me Big Data&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; google_fonts=&#8221;font_family:Montserrat%3Aregular%2C700|font_style:700%20bold%20regular%3A700%3Anormal&#8221;][vc_column_text]<\/p>\n<ul>\n<li>Architecture HADOOP et MapReduce<\/li>\n<li>Modes de stockage (NoSQL, HDFS)<\/li>\n<li>Collecte et transfert de donn\u00e9es (SQOOP, FLUME)<\/li>\n<li>Base et entrep\u00f4t de donn\u00e9es (HBase, Hive)<\/li>\n<\/ul>\n<p>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row][vc_column][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column][vc_custom_heading text=&#8221;Objectifs&#8221; google_fonts=&#8221;font_family:Montserrat%3Aregular%2C700|font_style:700%20bold%20regular%3A700%3Anormal&#8221;][vc_column_text] Comprendre les origines et les d\u00e9fis du traitement des donn\u00e9es massives. \u00c9tudier les fondements de l\u2019architecture HADOOP et de MapReduce. Maitriser le concept des bases de donn\u00e9es NoSQL. Introduire les algorithmes du Big Data Analytics. [\/vc_column_text][vc_custom_heading text=&#8221;Contenu&#8221; google_fonts=&#8221;font_family:Montserrat%3Aregular%2C700|font_style:700%20bold%20regular%3A700%3Anormal&#8221;][vc_row_inner][vc_column_inner width=&#8221;1\/3&#8243;][vc_custom_heading text=&#8221;Introduction au Big Data&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; google_fonts=&#8221;font_family:Montserrat%3Aregular%2C700|font_style:700%20bold%20regular%3A700%3Anormal&#8221;][vc_column_text] Origines et D\u00e9finitions Enjeux du Big Data [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":706,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-716","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/esi.ac.ma\/en\/wp-json\/wp\/v2\/pages\/716","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/esi.ac.ma\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/esi.ac.ma\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/esi.ac.ma\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/esi.ac.ma\/en\/wp-json\/wp\/v2\/comments?post=716"}],"version-history":[{"count":0,"href":"https:\/\/esi.ac.ma\/en\/wp-json\/wp\/v2\/pages\/716\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/esi.ac.ma\/en\/wp-json\/wp\/v2\/pages\/706"}],"wp:attachment":[{"href":"https:\/\/esi.ac.ma\/en\/wp-json\/wp\/v2\/media?parent=716"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}