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