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Test your basic knowledge |
Data Mining
Start Test
Study First
Subject
:
it-skills
Instructions:
Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can
study here
.
Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.
This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.
1. Which statement will take away user privileges to the database?
market basket analysis
Top-down approach
UNION
Revoke
2. Information about tables in the database is kept in the _____.
artificial Key
system catalog
The degree of granularity
Regression analysis
3. A single column that you create for an entity to serve as the primary key - because you otherwise would need many concatenated columns to do so - is called a(n) ____________.
data mining
ALTER TABLE Part DELETE Warehouse;
artificial Key
average error
4. A Star diagram has two types of tables (objects). They are called the___________________ tables and ; fact tables.
semantic object (SOL) attribute
dimension
Cartesian
MAE (Mean Absolute Error) deviation
5. These are considered an alternate storage techniques for data warehousing include.
Top-down approach
near-line secondary storage devices
decile chart
Referential integrity
6. The minimum cardinality and m is the maximum cardinality Cardinalities in Semantic Objects are shown as subscripts in the format n-m where _____
data visualization
ALTER TABLE Part DELETE Warehouse;
n
aggregate
7. Models that do ___________: MLR; KNN; Regression and Classification Trees; ANN; SVM
numeric prediction
machine learning
Group By
dimension
8. A synonym for data mining
Breakeven analysis
knowledge data discovery
Transformation
semantic object (SOL) attribute
9. 'Signatures' are used for intrusion detection by _______?
average error
market basket analysis
artificial Key
recognizing known patterns
10. Increased affordability of ____________ is a reason for the growth in popularity of data mining.
machine learning
degrees of summarization
knowledge data discovery
Document Analyzer
11. Gives an idea of systematic over- or under-prediction. Magnitude of average absolute error.
recognizing known patterns
Fact or Measurement table
data mart
average error
12. Which function should be used to calculate the total of all entries in a given column?
groves law
Revoke
drill-across report
Sum
13. __________ occurs when the initial scope of a project continues to expand as new features are incorporated into the project.
UNION
Scope creep
volatile data
near-line secondary storage devices
14. Organizes and analyzes data as an n-dimensional cube. The cube can be thought of as a common spreadsheet with two extensions: (1) support for multiple dimensions and (2) support for multiple concurrent users.
MOLAP
database administrator
drill-across report
UNION
15. Twice as likely to identify the important class (compared to avg. prevalence)
knowledge data discovery
decile chart
degrees of summarization
Count
16. An analytical-oriented organizational structure is a data warehouse _____________.
project readiness assessment factor
Into
average error
composite semantic objects
17. A _____________ is a system-generated primary key.
artificial Key
surrogate key
Sum
DROP TABLE Salesrep;
18. Which statement removes the table Salesrep from a DBMS?
DROP TABLE Salesrep;
degrees of summarization
database administrator
Horizontal integration
19. An ___________ relates two other objects.
Sum
association semantic object
database administrator
Insert
20. A powerful trend in IT is known as - which maintains that Computer transmission speed doubles every 18 months.
groves law
average error
ERD Modeling
volatile data
21. The _______________________ represents the source data for the DW. This layer is comprised - primarily - of operational transaction processing systems and external secondary databases.
decile chart
UNION
groves law
operational and external layer
22. A common example of the use of association methods where a retailer can mine the data generated by a point-of-sale system - such as the price scanner you are familiar with at the grocery store is referred to as:
Insert
maximum
market basket analysis
association semantic object
23. An economic feasibility measure. So is Internal rate of return.
PRIMARY KEY (CustomerNum)
UNION
lift charts
Breakeven analysis
24. Gives us an idea of the magnitude of errors. Actual value - estimated value.
neural networks & Decision Trees
Breakeven analysis
MAE (Mean Absolute Error) deviation
data mart
25. This is not considered one of the four major categories of processing algorithms and rule approaches.
Into
the relationship
Referential integrity
principle component analysis
26. ___________ is not a characteristic of a data warehouse.
Scope creep
Revoke
Regression analysis
volatile data
27. You can save the results of a query as a table by including the _____ clause in the query.
Into
PRIMARY KEY (CustomerNum)
neural networks & Decision Trees
Breakeven analysis
28. ___________ determines exactly what level of detail constitutes a fact record.
Document Analyzer
neural networks & Decision Trees
The degree of granularity
data mining
29. Which function calculates the number of entries in a table?
OLAP
The degree of granularity
Count
knowledge data discovery
30. A compound semantic object is an object that contains at least one ____.
Sum
Association
maximum
semantic object (SOL) attribute
31. R- squared(and adjusted r-squared) - A measure of how much of the variability around the target mean is explained by your predictive variables. Doesn't mean you have a good predictive model—only validation will tell you that
recognizing known patterns
performance metrics - Numeric Prediction
cascading delete
market basket analysis
32. The process by which numerical data is converted into graphical images is referred to as:
drill-across report
OLAP
data visualization
artificial Key
33. The ACCESS feature that tests to see if your tables are normalized properly is the ____.
Document Analyzer
performance metrics - Numeric Prediction
transformation mapping
project readiness assessment factor
34. The term _____ has been generally agreed to represent the broadest category of software technology that enables decision makers to conduct many dimensional analysis of consolidated enterprise data.
MOLAP
Transformation
OLAP
Regression analysis
35. ____________ would not normally be associated with ROUTINE data warehouse maintenance.
changing/UPDATE-ing
Into
Cartesian
recognizing known patterns
36. In general - ______________ are transformed to relations/tables by defining one relation for the object itself and another relation for each multivalued attribute.
database administrator
measuring predictive error
composite semantic objects
degrees of summarization
37. The deletion of a record that also deletes related records is referred to as a(n) _____.
data mining
cascading delete
system catalog
Insert
38. Within most organizations - the person known as the _____ determines the type of access various users can have to the corporate or enterprise database.
The degree of granularity
data mart
database administrator
Breakeven analysis
39. Which of the following database design and data warehouse design approaches is viewed to take a more strategic rather than operational perspective?
Top-down approach
dimension
Group By
numeric prediction
40. When an entity has a minimum cardinality of one it means the entity is required in _______.
knowledge data discovery
changing/UPDATE-ing
the relationship
average error
41. Not the same as goodness-of-fit; We want to know how well the model predicts new data - not how well it fits the data it was trained with; Key component of most measures is difference between actual y and predicted y (error)
measuring predictive error
semantic object (SOL) attribute
OLAP
composite semantic objects
42. _________ seeks to ensure that each application under development is fully integrated within its own boundaries and to eliminate any inconsistencies in the final software product.
Horizontal integration
project readiness assessment factor
measuring predictive error
Group By
43. The term "ETL" in data warehousing stands for: Extraction - ________________________ - & Loading.
lift charts
Transformation
market basket analysis
Referential integrity
44. ___________________ is used to relate one set of outcomes (dependent variable) to a set of predictor (independent) variables (e.g. - in time series analysis). Through this analysis we attempt to predictive future events - as the dependent variables b
surrogate key
Regression analysis
volatile data
data visualization
45. Generally Semantic Object Modeling (SOM) is consideredmore bottom-up oriented than _____________.
association semantic object
recognizing known patterns
the relationship
ERD Modeling
46. An alternative to the data warehouse concept is a lower-cost - scaled-down version referred to as the _____________.
data mart
transformation mapping
numeric prediction
knowledge data discovery
47. Which clause would be used to create groups of records?
Group By
artificial Key
data visualization
association semantic object
48. To add a new row to a table - use the _____ command.
Group By
The degree of granularity
recognizing known patterns
Insert
49. The product of two tables is also called the ________ product.
Transformation
Cartesian
ALTER TABLE Part DELETE Warehouse;
Group By
50. The process that records how data from operational data stores and external sources are transformed on the way into the warehouse is referred to as ________________.
transformation mapping
DROP TABLE Salesrep;
principle component analysis
aggregate