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