3 Review(s)

?. Overview and Concepts Data Warehousing and Business Intelligence Why re?ortinq and analysinq data. Raw data to valua?e information-Lifecycle of data WI1at is business intelliqence ?? and DW in today's perspect?ve What is data warehous?nq The builclin\I blocRs : l)efinin\I features 1),?t? warehouses c1ncl clata mc1rts Overview of the co?ponents - Metadata in the data warehouse - Need for data ware!1ous?nq - Basic elements of data wareho??sinq - Trends ?? data warehousinq. (Chapter - 1) 2. The Architecture of ?? and DW ?? ??c? DW ?rchitectures nncl its ty?es Re!Btion between ?? ??c? DW OLAI> (Online Analytical Processinq) definitions Difference between OLAP and OLTP Dimensional analysis What are cubes ? Drill-down and roll-up Slice and dice or rotation OLAP rnodels - ROLAP versus MOLAP - Definin?? sche?as : Stars, Snowflakes and fact constellations. (Chapter - 2) 3. lntroduction to Data Mining (DM) Motivation for d,lt? minin\I 1),Jt? minin?J-clefinition ancl functio11cllities Classific,ltion of DM systerns DM task prirnitil7es Inteqration of a data rnininq syste?1 witl1 a database or a data wareho??se - Iss??es ?? DM - KDD process. (Chapter - 3) 4. Data Pre-processing Why to ?re-?rocess dcJtB? Data clennin!J: Missin!J values. Noisy dnta Data inte???tion nnd transformation Data reduction : Data c??be aqqreqation, Dimensionality red??ction Data compression Numerosity reduction Data mininq primitives ?an\Iuaqes and system architectures : Task rele17ant data - Kind of knowledqe to be ?1ined - Discretization and concept h?erarchy. (Chapter - 4) 5. Concept Description and Association Rule Mining What is concept descr??tion ? - Data !Jeneralization and summarization-based characterization -Attribute relevance - Class comparisons association rule minin!J: Market basket analysis - Basic concepts - Findin!J frequent item sets : Apriori al!Jorithm - Generatin!J rules - lmproved Apr?ori al!Jorithm - Incremental ARM - Associative classification - Rule minin!J. (Chapter - 5)