Issues faced during data mining process

1. Major Issues in Data Mining

2. 1. Mining methodology
 Mining various and new kind of knowledge.
 Mining knowledge in multidimensional space.
 Data mining.
 Boosting the power of discovery in networked environment.
 Handling uncertainty, noise, or incompleteness of data.
 Pattern evaluation and pattern- or constraint –guided mining.

3. 2. User Interaction
 Interactive mining.
 Incorporation of background knowledge.
 Ad-hoc data mining and data mining query languages.
 Presentation and visualization of data mining results.

4. 3. Efficiency and Scalability
 Efficiency and scalability of data mining algorithm.
 Parallel, distributed, and incremental mining algorithm.
 Cloud computing and cluster computing.

5. 4. Diversity of Database types
 Handling complex types of data.
 Mining dynamic, networked, and global data repositories.

6. 5. Data mining and Society
 Social impacts of data mining.
 Privacy-preserving data mining.
 Invisible data mining.

7. Source
 The-Morgan-Kaufmann-Series-in-Data-Management-Systems-Jiawei-Han-
Micheline-Kamber-Jian-Pei-Data-Mining.-Concepts-and-Techniques-3rd-Edition-
Morgan-Kaufmann-2011