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