{"id":31369,"date":"2021-05-19T06:44:32","date_gmt":"2021-05-19T06:44:32","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/gi5002-big-data-analytics-syllabus-for-geoinformatics-6th-sem-2019-regulation-anna-university-professional-elective-ii\/"},"modified":"2021-05-19T06:44:32","modified_gmt":"2021-05-19T06:44:32","slug":"gi5002-big-data-analytics-syllabus-for-geoinformatics-6th-sem-2019-regulation-anna-university-professional-elective-ii","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/gi5002-big-data-analytics-syllabus-for-geoinformatics-6th-sem-2019-regulation-anna-university-professional-elective-ii\/","title":{"rendered":"GI5002: Big Data Analytics Syllabus for Geoinformatics 6th Sem 2019 Regulation Anna University (Professional Elective-II)"},"content":{"rendered":"

Big Data Analytics detailed syllabus for Geoinformatics Engineering (Geoinformatics) for 2019 regulation curriculum has been taken from the Anna Universities<\/a> official website and presented for the Geoinformatics students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below. <\/p>\n

For Geoinformatics Engineering 6th Sem scheme and its subjects, do visit Geoinformatics 6th Sem 2019 regulation scheme<\/a>. For Professional Elective-II scheme and its subjects refer to Geoinformatics Professional Elective-II syllabus scheme<\/a>. The detailed syllabus of big data analytics is as follows. <\/p>\n

Big data Analytics<\/title><\/p>\n<h4>Course Objective:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Unit I<\/h4>\n<p align=\"justify\">\n <strong>Introduction To Big Data<\/strong><br \/>\n Evolution of Big data – Best Practices for Big data Analytics – Big data characteristics – Validating – The Promotion of the Value of Big Data – Big Data Use Cases- Characteristics of Big Data Applications -Perception and Quantification of Value -Understanding Big Data Storage – A General Overview of High-Performance Architecture – HDFS – MapReduce and YARN – Map Reduce Programming Model\n<\/p>\n<h4>Unit II<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Unit III<\/h4>\n<p align=\"justify\">\n <strong>Association and Recommendation System<\/strong><br \/>\n Advanced Analytical Theory and Methods: Association Rules – Overview – Apriori Algorithm – Evaluation of Candidate Rules – Applications of Association Rules – Finding Association& finding similarity -Recommendation System: Collaborative Recommendation- Content Based Recommendation -Knowledge Based Recommendation- Hybrid Recommendation Approaches.\n<\/p>\n<h4>Unit IV<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Unit V<\/h4>\n<p align=\"justify\">\n <strong>Nosql Data Management for Big Data and Visualization<\/strong><br \/>\n NoSQL Databases : Schema-less Models||: Increasing Flexibility for Data Manipulation-Key Value Stores- Document Stores – Tabular Stores – Object Data Stores – Graph Databases Hive – Sharding –Hbase – Analyzing big data with twitter – Big data for E-Commerce Big data for blogs – Review of Basic Data Analytic Methods using R.\n<\/p>\n<h4>Course Outcome:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Text Books:<\/h4>\n<p align=\"justify\">\n<ol>\n<li>Anand Rajaraman and Jeffrey David Ullman, “Mir,iina of Massive Datasets”, Cambridge . University Press, 2012.<\/li>\n<li>David Loshin, “Big Data Analytics: From Strategic Planning to Enterprise Integration with Tools, Techniques, NoSQL, and Graph”, Morgan Kaufmann\/El sevier Publishers, 2013.<\/li>\n<\/ol>\n<h4>References:<\/h4>\n<p align=\"justify\">\n<ol>\n<li>EMC Education Services, “Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data”, Wiley publishers, 2015.<\/li>\n<li>Bart Baesens, “Analytics in a Big Data World: The Essential Guide to Data Science and its Applications”, Wiley Publishers, 2015.<\/li>\n<li>Dietmar Jannach and Markus Zanker, “Recommender Systems: An Introduction”, Cambridge University Press, 2010.<\/li>\n<li>Kim H. Pries and Robert Dunnigan, “Big Data Analytics: A Practical Guide for Managers ” CRC Press, 2015.<\/li>\n<li>Jimmy Lin and Chris Dyer, “Data-Intensive Text Processing with MapReduce”, Synthesis Lectures on Human Language Technologies, Vol. 3, No. 1, Pages 1-177, Morgan Claypool publishers, 2010.<\/li>\n<\/ol>\n<p align=\"justify\">For detailed syllabus of all the other subjects of Geoinformatics Engineering 6th Sem, visit <a class=\"rank-math-link\" href=\"..\/category\/geoinformatics+6th-sem\">Geoinformatics 6th Sem subject syllabuses for 2019 regulation<\/a>. <\/p>\n<p align=\"justify\">For all Geoinformatics Engineering results, visit <a class=\"rank-math-link\" href=\"https:\/\/www.inspirenignite.com\/anna-university\/anna-university-results\/\">Anna University Geoinformatics all semester results<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Big Data Analytics detailed syllabus for Geoinformatics Engineering (Geoinformatics) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the Geoinformatics students. For course […]<\/p>\n","protected":false},"author":2297,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[80],"tags":[],"class_list":["post-31369","post","type-post","status-publish","format-standard","hentry","category-geo"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/31369","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/users\/2297"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/comments?post=31369"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/31369\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=31369"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=31369"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=31369"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}