Computer Science & IT
Manuscript Writing
Biological & Life Science
Literature Review on Security Issues in Biometric Authentication
A Bayesian Approach in Internal Control Over Audit Reporting Quality
What are the challenges in data mining?
Types of Data Analysis: Methods and Techniques
Overview of Qualitative analysis
What are the Challenges in Data Mining?
1. Security and Social Challenges
Since dynamic approaches rely on data collection and sharing, it necessitates a high level of security. Client profiles, client standard of conduct explanation, illicit admittance to information, and the secret idea of information have become significant issues.
2. Noisy and Incomplete Data
Accurate data is truly heterogeneous, and it could include natural language text, time series, spatial data, temporal data, complicated data, audio or video, photos, and so on. It’s quite difficult to deal with all of these different forms of data while staying focused on what’s important. To isolate crucial information, new equipment and systems would almost always be required.
3. Distributed Data
In distributed processing, true data is generally stored at several stages. It could be on the internet, on individual computers, or even in databases. Because of technical and organizational challenges, moving all of the data to a consolidated data archive is difficult.
4. Performance
The efficiency of the approaches and algorithms used determines how the data mining framework is presented. If the strategies and algorithms planned are insufficient, it will have a negative impact on the presentation of the data mining measure.
5. Scalability and Efficiency of the Algorithms
The Data Mining technique should be scalable and efficient, to extract information from massive amounts of data in the data set,
6. Improvement of Mining Algorithms
The difficulty of data mining approaches, the massive size of the database, and the complete data flow encourage the spread and development of parallel data mining algorithms.
Even though data mining is amazing, it faces numerous difficulties during its usage. The difficulties could be identified with techniques used, methods, data, performance, and so on. The data mining measure becomes fruitful when the difficulties or issues are recognized accurately and figured out appropriately. As experienced service provider, we have a highly knowledgeable group of specialists who can construct a new or current excel database and apply various models. Tutors India experts will assist you in each part of your research project. We use our query tools to solve difficult business problems by applying established procedures of classification, clustering, regression, pattern recognition, and all other associated data mining principles.
Reference:
Sharma, Anu, M. K. Sharma, and R. K. Dwivedi. “Literature Review and Challenges of Data Mining Techniques for Social Network Analysis.” Advances in Computational Sciences and Technology 10, no. 5 (2017): 1337-1354.
