data mining problems and issues

on January 15, 2019 data warehousing and mining 1 comment

data mining problems and issues

Data mining is not an easy task, as the algorithm used can get very complete and data is not always available at one place.

It needs to be integrated from various hetrogenous data sources.

The major issues in data mining process are as the following:

Mining methodology and user interaction
Performance issues
Diverse data types issues
User interaction
Data types
Huge size of database
Wide distribution of data
High cost
Individual privacy
Data integrity

Some genuine and real data mining problems and issues are described below:-

data mining issues (problems)

The area of data mining is very large and its work is not easy. Every day, there is a large amount of data generation and store. So that the complexity of data mining is going on increasing and due to this there are issues and problems too. Let's read below that they have data mining issues .

data mining problems and issues

1: - The first issue of data mining is cost. because the queries of data mining are very complex, due to which data has to be collected and maintained in the data, and for all of us, we need large and fast systems which are very expensive.

2: - Handling unstable, uncompromising, and cost sensitive data is a major problem of data mining.

data mining problems and issues

3: - Another issue of data mining is the redundancy. It means duplication of lots of data of the same type of data.The same data is copied so that the original data is found and separated from them.

4: - The issue of privacy and security is very big. Everyone has to maintain the privacy and security of the organization and the organization.

5: - Managing bad data quality i.e. managing incomplete, unstable, noisy and high dimensional data.

6: - Trouble missing any data or access to data

data mining problems and issues

7: - Continuous updating of old data and handling new data.

8: - Processing large, hard, immovable and unorganized data in structured format.

9: - To do data mining, data miners should have background knowledge because this gives us complete information about the patterns of the data and the process. Without this background knowledge, this work is not easy.

10: - Data mining algorithm should be efficient and scalable. If it is not so, then we will neither benefit nor only negative results will come out.

11: - Every person needs different types of knowledge, therefore, data mining has to be discovered by the person as needed.