Download presentation
Presentation is loading. Please wait.
Published byDaniel Goodman Modified over 9 years ago
1
DBSQL 9-1 Copyright © Genetic Computer School 2009 Chapter 9 Data Mining and Data Warehousing
2
DBSQL 9-2 Copyright © Genetic Computer School, Singapore 2009 Chapter 9 Overview Data Analysis and Mining Architecture of Data Mining System Data Mining Functionalities Classification of Data Mining Systems How to Choose a Data Mining System Data Warehousing Data Warehouse Architecture Data Warehouse Design Classification of Data Warehouse Design User Interface
3
DBSQL 9-3 Copyright © Genetic Computer School, Singapore 2009 Data Mining The process of extracting or “mining” knowledge in a large amount of data.
4
DBSQL 9-4 Copyright © Genetic Computer School, Singapore 2009 Architecture of Data Mining
5
DBSQL 9-5 Copyright © Genetic Computer School, Singapore 2009 Data Mining Functionalities Characterization and discrimination Association analysis Classification and prediction Cluster analysis Outlier analysis Evolution analysis
6
DBSQL 9-6 Copyright © Genetic Computer School, Singapore 2009 Data Pre-processing Data pre-processing techniques Data Cleaning Data Integration Data Transformation Data Reduction
7
DBSQL 9-7 Copyright © Genetic Computer School, Singapore 2009 Areas where Data Mining is used Spatial Databases Multimedia Databases World Wide Web Sub-areas Telecommunication Industry Retail and more.
8
DBSQL 9-8 Copyright © Genetic Computer School, Singapore 2009 Coupling data mining with Database or Data Warehouse System The coupled components are seamlessly integrated into a uniform information-processing environment Data mining systems should be tightly coupled with a database system in the sense that the data mining and data retrieval processes are integrated by optimizing data mining queries deep into the iterative mining and retrieval process Tight coupling of data mining with OLAP-based data warehouse systems is also desirable so that data mining and OLAP operations can be integrated to provide OLAP mining features
9
DBSQL 9-9 Copyright © Genetic Computer School, Singapore 2009 Data Warehousing A Data Warehouse (DW) is a database that stores information oriented to satisfy decision-making requests It is constructed with the goal of storing and providing all the relevant information that is generated along the different databases of an enterprise. It is subject-oriented integrated time-variant non-volatile collection of data in support of management’s decision-making process.
10
DBSQL 9-10 Copyright © Genetic Computer School, Singapore 2009 Data Warehouse Architecture Inventory database Order entry database Production database Accounts payable database Operational Application Product Vendor CustomerFinancial Data Warehouse
11
DBSQL 9-11 Copyright © Genetic Computer School, Singapore 2009 The common data warehouse architecture are: Basic Data Warehouse Architecture Data Warehouse Architecture with a Staging Area Data Warehouse Architecture with a Staging Area and Data Marts
12
DBSQL 9-12 Copyright © Genetic Computer School, Singapore 2009 Classification of Data Warehouse Design Logical and Physical Design
13
DBSQL 9-13 Copyright © Genetic Computer School, Singapore 2009 User Interfaces Tools Traditional query and reporting tools On-line analytical processing, MOLAP, and ROLAP tools Data-mining tools Data-visualization tools Used to query and analyze the data stored in data warehouse.
14
DBSQL 9-14 Copyright © Genetic Computer School, Singapore 2009 End
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.