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