Data Mining Issues

Data Mining Issues-

In data mining data coming from lots of resources because of that data mining stick with different data mining issues.

Data mining issues divides in to 3 sections mainly-

1. Mining Methodology and User Interaction Issues

2. Performance Issues

3. Diverse Data Types Issues

We describe issue in detail below-

1. Mining Methodology and User Interaction Issues

a. Mining different kinds of knowledge in databases-  

Final output depend upon user requirement so in data mining lots of mining for better output is required.

b. Interactive mining of knowledge at multiple levels of abstraction-

Data mining always be a interactive because of better output for user.

c. Incorporation of background knowledge –

In data mining always used a background knowledge for describing final result. In descriptive data mining background knowledge discover for better result .

d.Data mining query languages and ad hoc data mining-

Data mining used a query languages for ad hoc mining . Query languages allowed in data mining task for better result but that time consuming.

e. Presentation and visualization of data mining results-

Data mining also need to visualize result for showing to user. each time needs to create pattern.

f. Handling noisy or incomplete data- 

Data mining needs to handle noisy and incomplete data because of data coming from different sources.

g.Pattern evaluation-

Pattern evaluation generation is need to show result to user each time.

2. Performance issue-

a. Efficiency and scalability of data mining algorithms –

Data mining needs to extract knowledge from different resources and different algorithm used for pattern evaluation, then maintain efficiency and scalability of algorithm is getting hard.

b. Parallel, distributed, and incremental mining algorithms-

Huge data coming from data warehouse so each time parallel distribution of data and distribution of data is get harder to data mining stage.

3. Diverse Data type issues-

a. Handling of relational and complex types of data-

Data mining allows data from different section that reason relations and each data type handled is harder.

b. Mining information from heterogeneous databases and global information systems –

User needs a exact pattern and accurate result for giving better decision for future, so data mining needs to collect information from lots of heterogeneous databases.