PRESENTATION ON
DATA WAREHOUSING
AND
DATA MINING
PRESENTED BY
SNEHALI CHAKE
PRIYANKA BONDRE
CHAHAT MADAN
KAUMUDI KAORE
DATA
DATA WAREHOUSING
A data warehousing is
subject oriented,
integrated, non -
volatile, time varying
collection of data in
support of its decision-
making process.
NEED OF DATA WAREHOUSING
Business user
Store historic data
Selective data
Make strategic decisions
ARCHITECTURE OF DATA WAREHOUSING
DATA WAREHOUSING
 Competitive advantage
 More cost effective
decision making.
 Better enterprise
intelligence
 Enhanced customer
service
 Time consuming
 Change resistance
 Complex
 Security issue
ADVANTAGES DISADVANTAGES
APPLICATIONS OF DATA WAREHOUSING
Standard reports and queries
Queries against summarized
data
Data mining
Interface with other data
warehouses
DATA MINING
Data mining refers
to extracting
knowledge from
large amount of
data, usually
automatically
gathered.
NEED OF DATA MINING
Operational
Decisional
Informational
Specific application
USER
ARCHITECTURE OF DATA MINING
USER INTERFACE
PATTERN EVALUATION
DATA MINING ENGINE
DATABASE OR DATA WAREHOUSE
SERVER
DATA CLEANSING,DATA SELECTION,DATA INTEGRATION
DATABASE
DATA
WAREHOUSE
WORLD WIDE WEB
OTHER
REPOSITORY
KNOWLEDGE
BASE
DATA MINING
 Automated forecasting
of trends and behavior.
 Automated
determination of earlier
unknown trends.
 Extensive depth and
breadth of data base.
 Privacy
 Misuse of information
 Inaccurate information
 Security.
ADVANTAGES DISADVANTAGES
APPLICATIONS
Marketing
Finance/Banking
Government
Medicine
Insurance and health care
Data warehousing and data mining

Data warehousing and data mining

  • 1.
    PRESENTATION ON DATA WAREHOUSING AND DATAMINING PRESENTED BY SNEHALI CHAKE PRIYANKA BONDRE CHAHAT MADAN KAUMUDI KAORE
  • 2.
  • 3.
    DATA WAREHOUSING A datawarehousing is subject oriented, integrated, non - volatile, time varying collection of data in support of its decision- making process.
  • 4.
    NEED OF DATAWAREHOUSING Business user Store historic data Selective data Make strategic decisions
  • 5.
  • 6.
    DATA WAREHOUSING  Competitiveadvantage  More cost effective decision making.  Better enterprise intelligence  Enhanced customer service  Time consuming  Change resistance  Complex  Security issue ADVANTAGES DISADVANTAGES
  • 7.
    APPLICATIONS OF DATAWAREHOUSING Standard reports and queries Queries against summarized data Data mining Interface with other data warehouses
  • 8.
    DATA MINING Data miningrefers to extracting knowledge from large amount of data, usually automatically gathered.
  • 9.
    NEED OF DATAMINING Operational Decisional Informational Specific application
  • 10.
    USER ARCHITECTURE OF DATAMINING USER INTERFACE PATTERN EVALUATION DATA MINING ENGINE DATABASE OR DATA WAREHOUSE SERVER DATA CLEANSING,DATA SELECTION,DATA INTEGRATION DATABASE DATA WAREHOUSE WORLD WIDE WEB OTHER REPOSITORY KNOWLEDGE BASE
  • 11.
    DATA MINING  Automatedforecasting of trends and behavior.  Automated determination of earlier unknown trends.  Extensive depth and breadth of data base.  Privacy  Misuse of information  Inaccurate information  Security. ADVANTAGES DISADVANTAGES
  • 12.