Data Knowledge discovery in databases is a broad process of finding useful knowledge from a collection of data. This is a process of discovering and identi

Data Knowledge discovery in databases is a broad process of finding useful knowledge from a collection of data. This is a process of discovering and identifying the ultimately important information from the observed results. According to Techopedia 2021, KDD encompasses data storage and access, scaling algorithms to massive data sets and interpreting results. It now houses many different approaches to discovery, which includes inductive learning, Bayesian statistics, semantic query optimization, knowledge acquisition for expert systems and information theory. The ultimate goal is to extract high-level knowledge from low-level data.

KDD includes multidisciplinary activities. 

2. Among the 10 motivation challenges that I have read based on my research, I chose “Fear of Failure” as a challenge. Being perfectionist and being afraid to commit mistakes is one of the most difficult challenges that a business person may face. We should always remember that we are not perfect and it is impossible for us to become perfect, but striving hard to be our best is a possible one. Failure is a part of our journey. We will be able to learn by trying and failing. Taking risk is an ultimate part of doing business. Once we take risks, we already accepted that we will experience some failures. So instead of fearing to failure, we just need to always do our best just like what Thomas Edison did and all other inspiring individuals.

3. Data mining integrates with the components of statistics and AL, ML, and Pattern Recognition in a way that data mining uses power of access list, machine learning, statistics and database techniques to mine large databases and come up with patterns. All of them are interesting data driven disciplines that help organizations make better decisions and positively affect the growth of any business.

4. Predictive is the use of statistics and modeling techniques to determine future performance based on current and historical data. This is important because it is use to determine what will be the performance of the company in the future and it is also helpful in making decisions in a variety of industries and disciplines. On the other hand, descriptive task allows you to display facts, figures, or knowledge. Its importance is to provide statistical data which help you to determine the current status of the business which are supported by facts. Both of these tasks are important and helpful in the aspects of the business.

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