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