Data Warehousing Data Mining And Olap Alex Berson Pdf

#Data Warehousing Data Mining And Olap Alex Berson Pdf series#

The amount of data doubles every 18 months, which affects response time and the sheer ability to comprehend its content.Decisions need to be made quickly and correctly.Business perspective вЂ“ In order to survive and succeed in todayвЂ™s highly competitive global environment:.Data Warehousing is an architectural construct of information systems that provides users with current and historical decision support information that is hard to access or present in traditional operational data stores.Introduction of Data Warehouse Data Warehouse and Business Data Warehouse Characteristics Seven Data Warehouse Components Decision support Systems & Data Warehouses, Ravindranath, B., New Age International Publishers, New Delhi.Indroduction to Data Warehousing Reference book: Data Warehousing, Data Mining and OLAP Alex Berson Stephen J. Data warehousing System Mallach 2000, McGraw Hill. 7.Дata Mining Pieter Adriaans & Dolf Zantinge 1997, Pearson Data Warehousing, Data Miniing and OLTP Alex Berson, 1997, McGraw Hill. Data Mining Techniques Arun Pujar 2001, University Press Hyderbad. Data Mining вЂ“ Concepts & Techniques Jiawei Han & Micheline Kamber вЂ“ 2001, Morgan Kaufmann. Data Warehousing in the Real World Sam Anahory & Dennis Murray 1997, Pearson 2.

#Data Warehousing Data Mining And Olap Alex Berson Pdf series#

Section вЂ“ D Mining Complex data objects, Spatial databases, Multimedia databases, Time series and Sequence data mining Text Data bases and mining Word Wide Web. Section вЂ“ C Data mining techniques: Association rules, Clustering techniques, Decision tree knowledge discovery through neural Networks & Genetic Algorithm, Rough Sets, Support Victor Machines and Fuzzy techniques. Data mining query languages, data specification, specifying knowledge, hierarchy specification, pattern presentation & visualization specification, data mining techniques, tools and applications. Section вЂ“ B Data mining definition & task, KDD versus data mining, data mining techniques, tools and applications. MOLAP types of OLAP, servers, 3 вЂ“ Tier data warehouse architecture, distributed and virtual data warehouses, data warehouse manager. Data warehouse process & architecture, OLTP vs. data warehouse, Data marts, Metadata, Multidimensional data mode, Data cubes, Schemas for Multidimensional Database: stars, snowflakes and fact constellations. Section вЂ“ A Data ware housing Definition, usage and trends, DBMS vs. Use of nonprogrammable calculators is allowed. For Candidates: Candidates are required to attempt five questions in all selecting one question from each of the sections A, B, C and D of the question paper and all the subparts of the questions in section E.

Section A, B, C and D will have two questions from the respective sections of the syllabus and each section will carry 15% of the total marks of the semester end examination for the course. Section E will be Compulsory, it will consist of a single question with 10-20 subparts of short answer type, which will cover the entire syllabus and will carry 40% of the total marks of the semester end examination for the course. For Paper Setters: The question paper will consist of five sections A, B, C, D, and E. Data Warehouse And Data Mining (IT-8003) Course CodeДҐ2 (1 Hr Each) (L= 39, T = 13 for each semester)Д¬ontinuous Assessment (based on sessional tests (2) 50%, Tutorials/Assignments 30%, Quiz/Seminar 10%, Attendance 10%)