2. Data Mining VS Data Warehousing
• Data Mining and Data Warehousing both are used to holds business intelligence
and enable decision making.
3. What is Data Minning ?
Also known as
knowledge discovery in
data (KDD).
Analyze trends
and patterns in
data
Done
automatically
using algorithm
Data Exploration
and Data Analysis
4. Who uses Data Mining ?
For Profit businesses
• Increases Profits.
• Improves customer experiences and loyalty.
Non-Profit businesses and charities
• Target correct group of people.
Example of how data mining is used
• Retail Stores
• Performing basket analysis
• Sales Forecasting
• Database Marketing
5. Process of Data Mining ?
They are six main steps in data mining
• Anomaly detection - Identify data that is unusual or considered errors.
• Association Rule – Searching for relationships between different parts of
the data.
• Clustering- Finding structures and relationships between different parts
of the data.
• Classification- placing new data among similar groups.
• Regression – Finding a common formula to model the data.
• Summarization – Making visual or written description of the data.
6. What is Data Warehousing ?
• Process of aggregating data and storing in a common
repository
• Data must be cleaned to correct errors and eliminate
noise
8. Data Warehousing Cont.
Several methods of organizing data for access.
• Data Mart
• Online Analytical Processing
• Online Transaction Processing
• Predictive Analysis
10. Why a separate Data Warehouse ?
High performance for both system.
• DBMS
• Warehouse
Different function and different data
• Missing data
• Data consolidation
• Data quality