Introduction
Data mining is the way for providing the solution from data based insight in the form of model, algorithms and pattern. Issues in data mining include performance issues, data security and privacy issues and data types issues. The major issue is noisy data that refers to useless data in the data. The study describes issues of data mining and the way data mining issues affect data analytics.
Question 1
Data mining is the way that can help in obtaining the information with huge volume of the data. The complication with data mining is that it provides with reality information that is heterogeneous, noisy and incomplete. The data in huge amounts are not accurate and reliable. These issues can be caused because of human mistakes and error of instruments that measure the data. In data mining, data is put away in various states in the distributed processing condition. It is required for carring out all data to be unified data because of organizational and technical reasons. Real world data can be heterogeneous and this includes multimedia that contains complex data, spatial data and temporal data. These data are hard to handle and include various kinds of data and require information. It required use is methodologies and tools for development to extract relevant information (Singh, Dubey & Sheetlani, 2018). Data is difficult to handle because it is hard to store because data are structured, unstructured and semi-structured. Poor data quality can be noisy data, missing value, dirty data and incorrect values that can result in poor representation of data sampling and inadequate size of data.
In data mining, there is difficulty in redundant data and it is integrated with conflicting from different forms and sources. Proliferation of privacy and security concerns can be raised that can result in unavailability of data and data are difficult to access. Scalability and efficiency of data mining algorithms, that can extract the information in huge amounts from the database. Even dealing with huge datasets need distributed approaches because the data can be unbalanced, cost-sensitive and non-static. It requires a high cost of maintaining and buying powerful servers, storage hardware and software that are required for handling large amounts of data. Processing can be complex for unstructured data. Data mining includes the process for extracting information that is obtained from large volume of data and in the real-world it can be incomplete, heterogeneous and noisy. Data present in large quantities can be unreliable and inaccurate. The problem can occur due to error of unstructured data that are used for measuring data and because of human errors. Alteration of data because of human and system error can result in incomplete and noisy data that makes data mining challenging (Pappalardo et al. 2021). It can be really hard to handle different kinds of data and extract required information. The performance of a data mining system depends on efficiency of techniques and algorithms used. If techniques and algorithms designed are not upto the mark then it can affect the performance of data mining process.
It is not an easy task and the entire algorithm used can be complex and data may not be available at one place. It is required to be interactive as it allows user to focus on searching for patterns for providing request for data mining that are based on returned results. The database contains multiple data objects and temporal data that are not possible for the system to mine for all kinds of data. The data source may be structured or unstructured that can add challenges to the data mining.
Question 2
Major data mining issues are not solely about security and privacy but components are vital. Data assortment transmission and sharing requires extra security. There might be sensitive details that are required for identifying a person and it is yet to present comprehensive tools that include unwelcomed onlookers. The next issue includes data incompletion and it results in improper information fixation. The information is sufficient but it can...