{"id":10791,"date":"2020-08-23T17:04:14","date_gmt":"2020-08-23T17:04:14","guid":{"rendered":"https:\/\/www.inspirenignite.com\/mh\/mca401-data-mining-and-business-intelligence-syllabus-for-mca-4th-sem-2017-pattern-mumbai-university\/"},"modified":"2020-08-23T17:04:14","modified_gmt":"2020-08-23T17:04:14","slug":"mca401-data-mining-and-business-intelligence-syllabus-for-mca-4th-sem-2017-pattern-mumbai-university","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/mh\/mca401-data-mining-and-business-intelligence-syllabus-for-mca-4th-sem-2017-pattern-mumbai-university\/","title":{"rendered":"MCA401: Data Mining and Business Intelligence Syllabus for MCA 4th Sem 2017 Pattern Mumbai University"},"content":{"rendered":"

Data Mining and Business Intelligence detailed Syllabus Scheme for Master of Computer Applications (MCA), 2017 regulation has been taken from the University of Mumbai<\/a> official website and presented for the MCA students. For Course Code, Course Title, Test 1, Test 2, Avg, End Sem Exam, Team Work, Practical, Oral, Total, and other information, do visit full semester subjects post given below. <\/p>\n

For all other Mumbai University MCA 4th Sem Syllabus 2017 Pattern, do visit MCA 4th Sem 2017 Pattern Scheme<\/a>. The detailed Syllabus Scheme for data mining and business intelligence is as follows.<\/p>\n

MCA401: Data Mining and Business Intelligence Syllabus for MCA 4th Sem 2017 Pattern Mumbai University<\/h2>\n

Data Mining and Business Intelligence<\/title><\/p>\n<h4>Prerequisites:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete Syllabus, results, class timetable, and many other features kindly download the <a 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 pdf platform to make students’s lives easier.<\/b><br \/><a 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>Course Educational Objectives (CEO):<\/h4>\n<p align=\"justify\">\nAt the end of the course, the students will be able to<\/p>\n<ol>\n<li>Acquire the knowledge of various concepts and tools behind data warehousing and mining data for business intelligence<\/li>\n<li>Study data mining algorithms, methods and tools<\/li>\n<li>Identify business applications of data mining<\/li>\n<\/ol>\n<h4>Course Outcomes:<\/h4>\n<p align=\"justify\">\nAt the end of the course, the students will be able to:<\/p>\n<ol>\n<li>Use conceptualization of BI techniques<\/li>\n<li>Apply data warehouse concepts for data analysis and report generation<\/li>\n<li>Develop industry level data mining skills using software tools<\/li>\n<li>Make use of relevant theories, concepts and techniques to solve real-world BI problems<\/li>\n<\/ol>\n<h4>1. Business Intelligence-<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete Syllabus, results, class timetable, and many other features kindly download the <a 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 pdf platform to make students’s lives easier.<\/b><br \/><a 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>2. Prediction methods and models for BI<\/h4>\n<p align=\"justify\">\nData preparation, Prediction methods-Mathematical method, Distance methods, Logic method, heuristic method-local optimization technique, stochastic hill climber, evaluation of models 06<\/p>\n<h4>3. BI using Data Warehousing<\/h4>\n<p align=\"justify\">\nIntroduction to DW, DW architecture, ETL Process, Top-down and bottom-up approaches, characteristics and benefits of data mart, Difference between OLAP and OLTP. Dimensional analysis- Define cubes. Drill- down and roll- up – slice and dice or rotation, OLAP models- ROLAP and MOLAP. Define Schemas- Star, snowflake and fact constellations. 08<\/p>\n<h4>4. Data Mining and Preprocessing<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete Syllabus, results, class timetable, and many other features kindly download the <a 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 pdf platform to make students’s lives easier.<\/b><br \/><a 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>5. Associations and Correlation<\/h4>\n<p align=\"justify\">\nAssociation rule mining:-support and confidence and frequent item sets, market basket analysis, Apriori algorithm, Incremental ARM, Associative classification- Rule Mining. 06<\/p>\n<h4>6. Classification and Prediction<\/h4>\n<p align=\"justify\">\nIntroduction, Classification methods:-Decision Tree- ID3, CART, Bayesian classification- Bayestheorem( Naive Bayesian classification),Linear and nonlinear regression. 08<\/p>\n<h4>7. Clustering<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete Syllabus, results, class timetable, and many other features kindly download the <a 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 pdf platform to make students’s lives easier.<\/b><br \/><a 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>8. Web mining and Text mining<\/h4>\n<p align=\"justify\">\nText data analysis and Information retrieval, text retrieval methods, dimensionality reduction for text. Web Mining: – web content, web structure, web usage. 04<\/p>\n<h4>Reference Books:<\/h4>\n<p align=\"justify\">\n<ul>\n<li>Business Intelligence data mining and optimization for decision making- by Carlo Vercellis ,wiley publication.<\/li>\n<li>Adaptive business Intelligence by ZbigniewMichlewicz, martin Schmidt, matthewmichal ewicz, constantinChiriac<\/li>\n<li>Data Mining concepts and techniques second edition by Jiawei Han and MichelineKamber.<\/li>\n<li>Data Mining:Introductory and Advanced topics, Pearson Education, by M.Dunham<\/li>\n<li>Data warehousing Fundamentals by PaulrajPonnian, John Willey<\/li>\n<li>Data mining for Business intelligence: concepts, techniques and applications in Microsoft Excel by G. Shumeli, N R Patel, P.C Bruce, Wiley<\/li>\n<\/ul>\n<h4>Assessment:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete Syllabus, results, class timetable, and many other features kindly download the <a 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 pdf platform to make students’s lives easier.<\/b><br \/><a 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<p align=\"justify\">For detail syllabus of all other subjects of Master of Computer Applications (MCA), 2017 regulation do visit <a href=\"..\/category\/mca+4th-sem\">MCA 4th Sem Subjects<\/a> syllabus for 2017 regulation.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data Mining and Business Intelligence detailed Syllabus Scheme for Master of Computer Applications (MCA), 2017 regulation has been taken from the University of Mumbai official website and presented for the […]<\/p>\n","protected":false},"author":2351,"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":[36,71],"tags":[],"class_list":["post-10791","post","type-post","status-publish","format-standard","hentry","category-4th-sem","category-mca"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/posts\/10791","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/users\/2351"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/comments?post=10791"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/posts\/10791\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/media?parent=10791"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/categories?post=10791"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/mh\/wp-json\/wp\/v2\/tags?post=10791"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}