Question

Which of the folowing is Nor true of data mining (DM) and DM process? Choose al that apply.

A. The term "data miving" appeared in the databate commundy in 1980 s.
B. DM works better on large amounts of data than on smal amounts.
C. OM is en ongoing business proceis which stare with data and then inloms actions through analytis which will create more data
d. the stage of data preparation, you need to gother your data assets, foduce datasets, clean your data, and refomal your data.
e. The goal of DM is to dicover putems and cules mesingtil for business, rother than any patiems in your data.
f. The first sieg in a DM process is data undentonding. which is couciat io a succesiha oM evicome but often ererlooked.

Answer 1

Contrary to statement B, data mining can work on both large and small datasets, although larger datasets typically yield more reliable patterns. Statement E is partially incorrect as the goal of data mining is not solely for business implications but also to find significant patterns within the data itself. Lastly, statement F is true; data understanding is a crucial first step in the data mining process.

Step-by-step explanation:

When considering which statements are not true of data mining (DM) and the DM process, it is important to recognize the real objectives and steps involved. Data mining first emerged in the database community in the 1980s, beginning a process that involves extracting meaningful patterns from large datasets to support decision-making. B is not true as DM can work with small amounts of data as well, but the accuracy and the patterns discovered might not be as profound as with larger datasets. The assertion that DM is an ongoing business process that starts with data and informs actions through analysis is correct (C); data mining is indeed a cyclical process that can lead to more data collection and subsequent analysis.

Data preparation (D) does indeed require gathering data assets, producing datasets, cleaning data, and reforming data, making this statement true. The goal of DM as stated in E is not fully true; although one aim is to discover patterns meaningful for business, data mining also seeks to identify any significant patterns within the data itself, not solely those with direct business implications. The first stage of the DM process is actually data understanding (F), which involves getting to know the data, its characteristics, and its quality before proceeding with mining.