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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. An economic feasibility measure. So is Internal rate of return.
Count
dimension
Into
Breakeven analysis
2. A synonym for data mining
volatile data
dimension
association semantic object
knowledge data discovery
3. Which data mining technique utilizes linkage analysis to search operational transactions for patterns with a high probability of repetition?
data visualization
machine learning
Association
project readiness assessment factor
4. The process by which numerical data is converted into graphical images is referred to as:
data visualization
semantic object (SOL) attribute
aggregate
data mining
5. A powerful trend in IT is known as - which maintains that Computer transmission speed doubles every 18 months.
principle component analysis
decile chart
ALTER TABLE Part DELETE Warehouse;
groves law
6. 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) ____________.
artificial Key
Sum
knowledge data discovery
machine learning
7. The _______________________ represents the source data for the DW. This layer is comprised - primarily - of operational transaction processing systems and external secondary databases.
operational and external layer
surrogate key
transformation mapping
average error
8. An alternative to the data warehouse concept is a lower-cost - scaled-down version referred to as the _____________.
data mart
numeric prediction
cascading delete
degrees of summarization
9. 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
data visualization
Breakeven analysis
ERD Modeling
10. Gives us an idea of the magnitude of errors. Actual value - estimated value.
decile chart
machine learning
Revoke
MAE (Mean Absolute Error) deviation
11. 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
DROP TABLE Salesrep;
Association
measuring predictive error
performance metrics - Numeric Prediction
12. The deletion of a record that also deletes related records is referred to as a(n) _____.
MAE (Mean Absolute Error) deviation
association semantic object
cascading delete
project readiness assessment factor
13. To add a new row to a table - use the _____ command.
Regression analysis
Insert
machine learning
performance metrics - Numeric Prediction
14. Which rule would you be violating - if you tried to delete a sales rep record - who currently has customers on file?
database administrator
cascading delete
project readiness assessment factor
Referential integrity
15. Generally Semantic Object Modeling (SOM) is consideredmore bottom-up oriented than _____________.
data visualization
data mart
ERD Modeling
Referential integrity
16. The ACCESS feature that tests to see if your tables are normalized properly is the ____.
aggregate
Document Analyzer
transformation mapping
groves law
17. Gives an idea of systematic over- or under-prediction. Magnitude of average absolute error.
data visualization
average error
groves law
OLAP
18. You can save the results of a query as a table by including the _____ clause in the query.
OLAP
MOLAP
Into
near-line secondary storage devices
19. A Star diagram has two types of tables (objects). They are called the___________________ tables and ; fact tables.
dimension
artificial Key
project readiness assessment factor
Document Analyzer
20. The product of two tables is also called the ________ product.
Cartesian
data mining
system catalog
degrees of summarization
21. An analytical-oriented organizational structure is a data warehouse _____________.
transformation mapping
measuring predictive error
project readiness assessment factor
knowledge data discovery
22. 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.
DROP TABLE Salesrep;
changing/UPDATE-ing
OLAP
UNION
23. 'Signatures' are used for intrusion detection by _______?
near-line secondary storage devices
market basket analysis
decile chart
recognizing known patterns
24. The term "ETL" in data warehousing stands for: Extraction - ________________________ - & Loading.
groves law
project readiness assessment factor
Transformation
principle component analysis
25. A ___________ combines result sets from more than one fact table.
drill-across report
semantic object (SOL) attribute
n
dimension
26. Which of the following database design and data warehouse design approaches is viewed to take a more strategic rather than operational perspective?
Regression analysis
operational and external layer
Top-down approach
semantic object
27. Models that do ___________: MLR; KNN; Regression and Classification Trees; ANN; SVM
Scope creep
semantic object
recognizing known patterns
numeric prediction
28. Which of the following is at the center of a star schema?
Sum
Count
Fact or Measurement table
knowledge data discovery
29. These are considered an alternate storage techniques for data warehousing include.
Regression analysis
Scope creep
aggregate
near-line secondary storage devices
30. Within most organizations - the person known as the _____ determines the type of access various users can have to the corporate or enterprise database.
machine learning
changing/UPDATE-ing
database administrator
volatile data
31. The set of activities used to find new - hidden - or unexpected patterns in data is referred to as _____.
recognizing known patterns
data mining
Transformation
association semantic object
32. An ___________ relates two other objects.
Insert
association semantic object
maximum
changing/UPDATE-ing
33. Are a data mining technology.
neural networks & Decision Trees
lift charts
data mining
groves law
34. 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)
data mining
measuring predictive error
Insert
ALTER TABLE Part DELETE Warehouse;
35. ____________ would not normally be associated with ROUTINE data warehouse maintenance.
changing/UPDATE-ing
Revoke
data mart
the relationship
36. On an ER Diagram the number (mark) on relationship line that is farthest away from each entity (rectangle) represents the _______ cardinality.
ERD Modeling
maximum
database administrator
recognizing known patterns
37. _________ 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.
drill-across report
semantic object
Referential integrity
Horizontal integration
38. To create the primary key clause for the Customer table on the CustomerNum field - which of the following is the correct statement?
PRIMARY KEY (CustomerNum)
Count
drill-across report
Transformation
39. Which statement removes the table Salesrep from a DBMS?
Breakeven analysis
Association
aggregate
DROP TABLE Salesrep;
40. Which clause would be used to create groups of records?
composite semantic objects
system catalog
Group By
market basket analysis
41. Useful for assessing performance in terms of identifying the most important class. Helps such choices as: How many tax records to examine; How many loans to grant; How many customers to mail an offer
Referential integrity
lift charts
data mining
MAE (Mean Absolute Error) deviation
42. This is not considered one of the four major categories of processing algorithms and rule approaches.
groves law
principle component analysis
data mart
Regression analysis
43. Why are Star Schemas so useful in Financial Planning and Accounting Information Systems?
market basket analysis
degrees of summarization
The degree of granularity
aggregate
44. In general - ______________ are transformed to relations/tables by defining one relation for the object itself and another relation for each multivalued attribute.
near-line secondary storage devices
composite semantic objects
PRIMARY KEY (CustomerNum)
neural networks & Decision Trees
45. Semantic object link (SOL) attributes establish a relationship between one _______ and another.
artificial Key
ALTER TABLE Part DELETE Warehouse;
groves law
semantic object
46. ___________ determines exactly what level of detail constitutes a fact record.
near-line secondary storage devices
artificial Key
Insert
The degree of granularity
47. The minimum cardinality and m is the maximum cardinality Cardinalities in Semantic Objects are shown as subscripts in the format n-m where _____
near-line secondary storage devices
cascading delete
Breakeven analysis
n
48. The SQL command for deleting the Warehouse field from the Part table is _____.
volatile data
transformation mapping
ALTER TABLE Part DELETE Warehouse;
Sum
49. __________ occurs when the initial scope of a project continues to expand as new features are incorporated into the project.
Scope creep
numeric prediction
data visualization
transformation mapping
50. The _____ operation of two tables results in a single table with the same columns as the first table - and containing all rows that are in the first table merged with all the rows in the second table - minus any duplicate rows.
UNION
Horizontal integration
Regression analysis
Document Analyzer