data warehouse
TRANSCRIPT
DATA WAREHOUSE
bySonali Chawla
INTRODUCTION TO DATA WAREHOUSE Subject-oriented Integrated Time Variant Non Volatile
DATA WAREHOUSE CONCEPTS Operational Data and Informational Data Difference between Operational Data and
Data Warehouse Why have a separate Data Warehouse?
DATA WAREHOUSE ARCHITECTURE Steps of the Design and Construction of Data
Warehouse The design of data warehouse The process of data warehouse design
Three tier architecture Model
Enterprise Warehouse Data Marts Virtual Warehouse
Metadata Repository Data Warehouse Back-End Tools and Utilities
Data Extraction Data Clearing Data Transformation Load Refresh
Advantages of Building Data Warehouse Data Warehouse Application
Information Processing Analytical Processing Data Mining
DATABASE DATA MODELING Star Schema Snowflake Schema Facts Constellation Schema
OLAP AND DATA CUBE OLAP Data Cube Measures
Distributive Algebraic Holistic
Concept Hierarchies
Operations on Cubes
Roll Up Drill Down Slice and Dice Pivot (rotate) Drill Across Drill Through
OLAP Server Relational OLAP Server Multidimensional OLAP Server Hybrid OLAP Server
DATA PROCESSING Data Cleaning
Look for Missing Values Ignore the tuples Fill in the missing values manually Use a global constant to fill in the missing values Use the attribute mean to fill the missing values Use the attribute mean for all samples belonging to
the same class as given tuple Use the most probable value to fill in the missing value
Noisy Data
Binning Smoothing by bin mean Smoothing by bin boundaries
Regression Linear Multiple Linear
Clustering
Data Integration
Entity Identification Problem Redundancy Detection and Resolution of Data value conflicts
Data Transformation Smoothing Aggregation Generalization Normalization Attribute Construction
Data Reduction
Data cube aggregation Attribute Subset Selection Dimensionality Reduction Numerosity Reduction Discretization and concept hierarchy generation