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Paper Presentation for Data Mining and Data Warehosuing.
Citation preview
Yogesh BenawatSameer Deshmukh
Outline
Data Mining Data Warehousing Q ‘n’ A Conclusion
Historical Perspective
1960s: Data collection, database creation, IMS
and network DBMS 1970s:
Relational data model, relational DBMS implementation
1980s: RDBMS, advanced data models
(extended-relational, OO, deductive, etc.) and application-oriented DBMS (spatial, scientific, engineering, etc.)
1990s—2000s: Data mining and data warehousing,
multimedia databases, and Web databases
Data Mining
Definition
Data mining automates the process of locating and extracting the hidden patterns and
knowledge
In simple words Searching for new knowledge
Why we need data mining
Data explosion problem
Automated data collection tools and mature database
technology lead to tremendous amounts of data stored in
databases, data warehouses and other information repositories
We are drowning in data, but starving for knowledge!
Solution: Data mining
Data warehousing and on-line analytical processing
Extraction of interesting knowledge (rules, regularities,
patterns, constraints) from data in large databases
Data Mining Models
Predictive Model
Descriptive Model
Predictive Model
Prediction determining how certain attributes will behave in the
future Regression
mapping of data item to real valued prediction variable
Classification categorization of data based on combinations of
attributes Time Series analysis
examining values of attributes with respect to time
Descriptive Model
Clustering most closely data clubbed together into clusters
Data Summarization extracting representative information about
database Association Rules
associativity defined between data items to form relationship
Sequence Discovery it is used to determine sequential patterns in data
based on time sequence of action
Data mining process
Problem Definition
Creating Database
Exploring database
Preparation for creating a data mining model
Building Data Mining Model
Evaluation Phase
Deploying the Data Mining model
Fig. General Phases of Data Mining Process
Who needs data mining?
Whoever has information fastest and uses it wins
Don McKeough former president of Coke Cola
Businesses are looking for new ways to let end users find the data they need to:
make decisions Serve customers Gain the competitive edge
Applications
Business analysis and management Computer security Customer relationships analysis and
management Telecommunication analysis and management News and entertainment Bioinformatics and Healthcare analysis
Summary
Need of data mining Data mining models Process of data mining Some applications
Data Warehousing
Data Warehousing Data Warehouse
What is Data Warehouse? Database & Data Warehouse.
How to distinguish? Purpose
Database : Transactional Data Warehouse :Intended for Decision
Supporting Applications. Functionality
Optimized for data retrieval, not routine transaction processing.
Structure Performance
Data Warehousing Modern Organization’s needs ?
Companies spread world wide. Have
So many Data Sources Different Operational Systems Different Schemas
Need Data for Complex Analysis Knowledge Discovery Decision Making.
Solution ???
Data Warehousing Solution…Data Warehouse. Data Warehouse . Definition ??
No single definition…. Data Warehouse
Collection of Information gathered from multiple sources, stored under unified schema, at a single site & mainly intended for decision support applications.
A subject oriented, integrated, nonvolatile, time-variant, collection of data in support of management’s decision. ~ W.H. Inmon
Warehouses are Very Large Databases
35
%
30
%
25
%
20
%
15
%
10
%
5%
0%
5GB
5-9GB
10-19GB 50-99GB 250-499GB
20-49GB 100-249GB500GB-1TB
Initial
Projected 2Q96
Source: META Group, Inc.
Res
pond
ents
Data Warehousing Data Warehouse -
Architecture
DataSource1
DataSourcen
DataSource 2
Data Warehouse
Data Loaders
DBMS
Data
Data
DataMining
OLAP
DSSIESI
.
.
.
Data Warehousing Data Warehouse building
When & how to gather data Source-driven architecture Destination-driven architecture
What schema to use Data Cleansing
Task of correcting and processing data How to propagate updates What data to summarize And many more……
Summary
What is Data Warehousing? Data Warehouse. Data Warehouse – Architecture Data Warehouse vs. Data Mining
Conclusion
Your data is full of undiscovered gems; start digging!
References
Data Mining Introductory and advanced Topics Margaret H. Dunham Modern Data Warehousing, Mining, and visualization
George M. Marakas
Data Mining BPB Publications
Database System Concepts Silbershatz, Korth,
Sudarshan www.statoo.info/ www.crm2day.com/ www.trilliumsoftware.com/
Q ‘n’ A
Thank You!