Data Mining is a sub-field in computer science. The traditional database can query limited information from the database using SQL. At best, you can write complex queries and get results.
When the size of the database grow the traditional DBMS does not help.
The goal of data mining is to extract meaningful information from a large data set and present it in a useful and understandable manner.
Why to learn Data Mining?
Data mining has become very important in last few years because there has been an exponential increase in data from various sources and also, the data storage technology is also improving day-by-day.
Business Organizations and various institutions are interested in discovering interesting information from their huge data-sets. There is a huge demand for data mining, big data and data analytics professionals.
The tutorial is focused on the process of discovering data patterns which includes
- Data Mining
- Interpretation or Evaluation
Data Mining Topics
A list of data mining topics are given below. Read from top to bottom.
Introduction To Data Mining
- Data mining overview.
- What are the steps in data mining.
- Data mining architecture and its components.
- Kind of data in data mining.
- Kind of patterns in data mining.
Data Warehouse Concepts
- Difference between OLTP and OLAP.
- Operational database vs. Data warehouse.
- Dirty data and data cleaning.
- Transformation algorithms.
- Integration of data sources in data mining.