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