What do you know about Data Mining? - Part 2
How much did you know about Data Mining? Keep testing your knowledge with Quantrimang through the following multiple choice questions!
- Question 1: KDD is the abbreviation of any technique in Data Mining?
- Knowledge Data Developer
- Knowledge Develop Database
- Knowledge Discovery Database
- There is no right answer
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- Question 2: Which of the following statements is true about KDD?
- Output of KDD is data.
- Output of KDD is query.
- The output of KDD is information.
- The output of KDD is potentially valuable information.
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- Question 3: Where is not an application of Data Warehouse?
- Information processing - Information processing
- Processing data analysis - Analytical processing
- Transaction processing - Transaction processing
- Data mining - Data mining
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- Question 4: Choose the correct answer:Data can be updated in the operational environment (Operational Environment).
- It's correct
- False
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- Question 5: How many stages does KDD process have?
- 3
- 4
- 5
- 6
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- Question 6: Transient data is what data type?
- The data created in the session with the application and stored in the database after the application ends.
- Is the data created in the session with the application but not stored in the database after the application ends.
- Data is never changed or deleted after they are added.
- Data is never deleted after they are added.
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- Question 7: Data Warehouse architecture based on:
- Database Management System - DBMS
- RDBMS - Relational Database Management System
- Structured query language - SQL
- ORACLE Database Management System
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- Question 8: What kind of database can be used for data warehouse optimization and OLAP?
- Retional Database
- Relational Database
- Structural Database
- Multidimensional Database
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- Question 9: ODS stands for:
Online Data Store- Online Data Storage
- Operational Data Stand
- Operational Data Store
- Question 10: A subset of the Data Warehouse data warehouse contains all data on a specific topic called:
- Data Pocket
- Metadata
- Data Mart
- Data Mining
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