Name: Notes for Data Mining And Data Warehousing - DMDW by Verified Writer
Rating: 3.8 (109 reviews)
Author: Verified Writer

Overview: Data warehousing, The compelling need for data warehousing, the Building blocks of data warehouse, data warehouses and data marts, overview of the components, metadata in the data warehouse, trends In data warehousing, emergence of standards, OLAP, web enabled data warehouse, Introduction to the data warehouse project, understanding data warehousing Architecture, Data warehousing implementation, from data warehousing to data mining.

Overview Data Warehousing

Components Of Data Warehouse

Introduction to Data mining, Data mining Functionalities, Data preprocessing (data
summarization, data cleaning

Introduction To Data Mining

Data cleaning, data integration and transformation, data reduction,
data discretization

Data Preprocessing

Mining frequent patterns, associations, correlations (market basket analysis, the
apriori algorithm, mining various kinds of association rules, from association mining
to correlation analysis)
Classification: classification by decision tree induction, Rule based classification

Mining Frequent Pattern

Cluster Analysis: types of data in cluster analysis, A categorization of major
clustering methods(partitioning methods, hierarchical methods),clustering high
dimensional data, outlier analysis
Advanced techniques: web mining, spatial mining, temporal mining, Data mining
applications in (financial data Analysis, retail industry, telecommunication industry,
Biological data analysis, intrusion detection, in other scientific applications)

Cluster Analysis

Outlier Detection

I had complete rs 29 but unable to download plesae solve the problem

top and bottom line are cut this makes them bad otherwise good

Verified Writer

B.Tech

Notes for Data Mining And Data Warehousing - DMDW by Verified Writer 

Notes for Data Mining And Data Warehousing - DMDW by Verified Writer

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DMDW