Data warehousing is a method of organizing and compiling data into one database, whereas data mining deals with fetching important data from databases. Data mining attempts to depict meaningful patterns through a dependency on the data that is compiled in the data warehouse.
unit-1:
Data Warehousing and Business Analysis
unit-2:
Data Mining
unit-3:
Classification and Prediction
unit-4:
Cluster analysis
unit-5:
Mining Object, Spatial, Multimedia, Text and Web Data
unit-1:
Data Warehousing and Business Analysis: Data warehousing Components
–Building a Data warehouse
–Data Warehouse Architecture no
– DBMS Schemas for Decision Support
– Data Extraction, Cleanup, and Transformation Tools
–Metadata
– reporting
– Query tools and Applications
– Online Analytical Processing (OLAP)
– OLAP and Multidimensional Data Analysis.
unit-2:
Data mining:
-Data mining functionalities
-Data preprocessing
-Data cleaning
-Data integration and transformation
-Data Reduction
-Data discritization and concept hierarchy generation
-Architecture of a typical data mining system
-Classification of Data mining systems
Rule mining:
-Efficient and scalable Frequent Item set mining methods
-mining various kinds of Association rules
-Association mining to correlation Analysis
-Constraint,Based Association mining
Telegram link:https://t.me/themanchinebrain
daily notes will be available in telegram
