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