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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 function calculates the number of entries in a table?
composite semantic objects
OLAP
The degree of granularity
Count
2. Twice as likely to identify the important class (compared to avg. prevalence)
artificial Key
decile chart
Group By
PRIMARY KEY (CustomerNum)
3. An analytical-oriented organizational structure is a data warehouse _____________.
aggregate
project readiness assessment factor
ERD Modeling
numeric prediction
4. ___________________ 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
Regression analysis
machine learning
n
changing/UPDATE-ing
5. 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.
ALTER TABLE Part DELETE Warehouse;
UNION
MAE (Mean Absolute Error) deviation
composite semantic objects
6. These are considered an alternate storage techniques for data warehousing include.
the relationship
UNION
near-line secondary storage devices
MAE (Mean Absolute Error) deviation
7. An alternative to the data warehouse concept is a lower-cost - scaled-down version referred to as the _____________.
numeric prediction
database administrator
Regression analysis
data mart
8. 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.
performance metrics - Numeric Prediction
Horizontal integration
MOLAP
database administrator
9. The ACCESS feature that tests to see if your tables are normalized properly is the ____.
dimension
Document Analyzer
data mart
aggregate
10. __________ occurs when the initial scope of a project continues to expand as new features are incorporated into the project.
Scope creep
data mining
artificial Key
groves law
11. Which rule would you be violating - if you tried to delete a sales rep record - who currently has customers on file?
PRIMARY KEY (CustomerNum)
Horizontal integration
knowledge data discovery
Referential integrity
12. In general - ______________ are transformed to relations/tables by defining one relation for the object itself and another relation for each multivalued attribute.
Transformation
Scope creep
composite semantic objects
Regression analysis
13. The set of activities used to find new - hidden - or unexpected patterns in data is referred to as _____.
data mining
artificial Key
recognizing known patterns
ERD Modeling
14. Models that do ___________: MLR; KNN; Regression and Classification Trees; ANN; SVM
maximum
Transformation
aggregate
numeric prediction
15. Which of the following is at the center of a star schema?
measuring predictive error
Fact or Measurement table
principle component analysis
volatile data
16. ____________ would not normally be associated with ROUTINE data warehouse maintenance.
operational and external layer
dimension
Revoke
changing/UPDATE-ing
17. The term "ETL" in data warehousing stands for: Extraction - ________________________ - & Loading.
Transformation
Breakeven analysis
Horizontal integration
transformation mapping
18. To create the primary key clause for the Customer table on the CustomerNum field - which of the following is the correct statement?
OLAP
PRIMARY KEY (CustomerNum)
Document Analyzer
The degree of granularity
19. 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:
Document Analyzer
market basket analysis
dimension
DROP TABLE Salesrep;
20. 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) ____________.
average error
Count
artificial Key
dimension
21. The minimum cardinality and m is the maximum cardinality Cardinalities in Semantic Objects are shown as subscripts in the format n-m where _____
Document Analyzer
project readiness assessment factor
data mart
n
22. Gives us an idea of the magnitude of errors. Actual value - estimated value.
drill-across report
MAE (Mean Absolute Error) deviation
The degree of granularity
Horizontal integration
23. ___________ determines exactly what level of detail constitutes a fact record.
Insert
semantic object (SOL) attribute
average error
The degree of granularity
24. 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)
Count
Transformation
measuring predictive error
transformation mapping
25. An economic feasibility measure. So is Internal rate of return.
market basket analysis
principle component analysis
changing/UPDATE-ing
Breakeven analysis
26. The _______________________ represents the source data for the DW. This layer is comprised - primarily - of operational transaction processing systems and external secondary databases.
knowledge data discovery
volatile data
semantic object
operational and external layer
27. 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
performance metrics - Numeric Prediction
principle component analysis
market basket analysis
PRIMARY KEY (CustomerNum)
28. Which clause would be used to create groups of records?
the relationship
Group By
semantic object
association semantic object
29. Which statement removes the table Salesrep from a DBMS?
maximum
the relationship
degrees of summarization
DROP TABLE Salesrep;
30. Which statement will take away user privileges to the database?
Revoke
The degree of granularity
surrogate key
groves law
31. 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
DROP TABLE Salesrep;
numeric prediction
the relationship
lift charts
32. _________ 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.
PRIMARY KEY (CustomerNum)
Horizontal integration
measuring predictive error
ALTER TABLE Part DELETE Warehouse;
33. An ___________ relates two other objects.
data mining
Breakeven analysis
association semantic object
groves law
34. A ___________ combines result sets from more than one fact table.
data mining
drill-across report
semantic object (SOL) attribute
surrogate key
35. A compound semantic object is an object that contains at least one ____.
semantic object (SOL) attribute
OLAP
degrees of summarization
recognizing known patterns
36. The SQL built-in functions - which may appear on the same line as the SELECT statement (before the FROM clause) are called _____ functions.
drill-across report
near-line secondary storage devices
operational and external layer
aggregate
37. 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 ________________.
the relationship
data visualization
dimension
transformation mapping
38. Are a data mining technology.
market basket analysis
Insert
near-line secondary storage devices
neural networks & Decision Trees
39. A powerful trend in IT is known as - which maintains that Computer transmission speed doubles every 18 months.
data mart
groves law
Into
cascading delete
40. Gives an idea of systematic over- or under-prediction. Magnitude of average absolute error.
near-line secondary storage devices
Cartesian
average error
association semantic object
41. A Star diagram has two types of tables (objects). They are called the___________________ tables and ; fact tables.
Fact or Measurement table
changing/UPDATE-ing
UNION
dimension
42. The SQL command for deleting the Warehouse field from the Part table is _____.
knowledge data discovery
ALTER TABLE Part DELETE Warehouse;
market basket analysis
composite semantic objects
43. ___________ is not a characteristic of a data warehouse.
volatile data
aggregate
Horizontal integration
degrees of summarization
44. A synonym for data mining
knowledge data discovery
maximum
OLAP
principle component analysis
45. This is not considered one of the four major categories of processing algorithms and rule approaches.
recognizing known patterns
system catalog
principle component analysis
Insert
46. When an entity has a minimum cardinality of one it means the entity is required in _______.
numeric prediction
data visualization
the relationship
artificial Key
47. The process by which numerical data is converted into graphical images is referred to as:
Sum
Top-down approach
data visualization
Regression analysis
48. On an ER Diagram the number (mark) on relationship line that is farthest away from each entity (rectangle) represents the _______ cardinality.
maximum
dimension
Breakeven analysis
knowledge data discovery
49. A _____________ is a system-generated primary key.
Revoke
Referential integrity
principle component analysis
surrogate key
50. The product of two tables is also called the ________ product.
operational and external layer
MOLAP
Cartesian
UNION