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