Description
1)The readings this week discusses broad context of risk and investigative forensics. Part of risk management is to understand when things go wrong, we need to be able to investigate and report our findings to management. Using this research, or other research you have uncovered discuss in detail how risk and investigate techniques could work to help the organization. ERM helps to protect an organization before an attack, where as forensics investigate technique will help us after an attack - so lets discus both this week.
2)Research and explain the term "Data Mining Query Language" and how is it used in Data Mining.
Explanation & Answer
Attached. Please let me know if you have any questions or need revisions.
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DATA MINING QUERY LANGUAGE
Student’s Name
Course Code
Professor
March 2, 2021
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DATA MINING QUERY LANGUAGE
Data Mining Query Language
Data mining query language is a language that is applied in data mining. It is built upon
the foundation of the structured query language. Data mining query language is designed in order
to enable interactive data mining and ad hoc. The commands for specifying primitives in data
mining are provided by the data mining query language. The data mining query language was
initially a suggestion of Han, Fu and Wang. This was proposed to be used by the database miner
data mining system. The SQL-like syntax is adapted by the data mining query language.
In data mining, the data mining query language is used when working with data
warehouses and databases. The first role that is played by the data mining query language in data
mining is defining the data mining tasks (Pisoni, 2019). These are the tasks that are to be
completed in order for the data mining to be achieved or smoothly carried out. In this case, data
mining query language is used to define tasks in data marts and in data warehouses.
Data mining query language is al...
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