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