1. Which of the following options relate to the immediate data extraction technique of ETL functions in the data warehouse?
Data capture through transaction logs
Data capture through database triggers
Data capture in source systems
ALL OF THE ABOVE
2. Which of the following are major steps in the ETL process in the data warehouse?
I. Determine all the data sources, both internal and external
II. Establish data transformation and cleansing rules III.Plan for aggregate or summary tables
IV. Write procedures for all data loads
V. Plan datafeeds from the data warehouse to downstream MDDBs
I, II, III, IV
II, III, IV, V
I, III, IV, V
I, II, III, V
3. Which of the following applies to the methods for data capture based on date and time stamping from source systems as part of the ETL functions in the data warehouse?
Transaction logs must be set up
Major revisions to existing source applications likely
Performance of source systems greatly affected
NONE OF THE ABOVE
4. As part of storage management during the growth and maintenance phase of the data warehouse project, if it is a distributed environment with multiple servers having individual pools, it is preferable to connect the servers to a single storage pool that can be accessed intelligently.
True
False
5. Similar to OLTP systems, executive and senior management staff are excluded from user training.
True
False
6. With respect to user training courses in the data warehouse project, which of the following is NOT suitable for an introductory course?
Browsing of warehouse contents
Predefined queries
Details of source system platforms
Data warehousing overview
7. With regard to physical model components of the data warehouse, which of the following is the correct matching of physical data structure and the corresponding data storage area?
Load image flat file Data Warehouse Repository
Virtual sequential access file Data Staging Area
Proprietary matrix file OLAP
Source system extract flat file Downstream application
8. With regard to using RAID technology for data storage in the data warehouse, which of the following refers to the basic features of this technology?
I.Disk aggregating
II.Disk mirroring
III.Disk duplexing
IV.Parity checking
V.Disk striping
I, II, III, IV
II, III, IV, V
I, II, IV, V
I, II, III, V
9. Bitmapped indexes are more suitable for the data warehouse environment than for an OLTP system.
True
False
10. The following are significant objectives of the physical design process of the data warehouse EXCEPT:
Ensuring performance
Managing storage
Providing scalability
Establishing source system data extractions
11. Which of the following refers to characteristics of data quality in the data warehouse?
A data item is exact fit for the purpose business users have defined it
Enables quick and easy data retrieval
Relates to the system as a whole
BOTH A and C
12. Which of the following is the correct matching of data quality dimension in the data warehouse and the corresponding meaning?
Domain integrity values of a data item same across all source systems
Consistency duplication of records completely resolved
Data anomaly a data field not used only for the purpose for which it is defined
Completeness same data not stored in more than one place in the system
13. Which of the following is the correct matching of type of data quality problem in the data warehouse and the corresponding example of the problem?
Dummy values in fields value 99999 in zip code field for European customer
Contradicting values store codes and product codes in the same field
Inconsistent values user comments entered in the field for contact name
Multipurpose fields a California state code and New Jersey zip code for the same customer
14. In the initial user support arrangement that is set up during the deployment phase of the data warehouse project, which of the following is the correct matching of point of support and its corresponding support role?
Hotline support first point of contact within department
Managerial support information on query templates and how to use them
Technical support provide support on hardware, system software, and tools
User representative resolve issues not resolved by technical support
15. The following represent actions during user acceptance testing for the deployment of the data warehouse EXCEPT:
Users in each department to run and test typical queries and reports
Each user group to test a subset of predefined queries and preformatted reports
Users to test data clustering in the database
Users to test thirdparty frontend tools and interfaces
16. In order to speed up the initial data load of the data warehouse, it is a good practice to suspend referential integrity verification during the load process.
True
False
17. Among the many different definitions for metadata in the data warehouse, which of the following does NOT indicate what metadata is?
Data warehouse atlas
Data warehouse tools
Data warehouse roadmap
Data warehouse directory
18. Which of the following types of information from metadata indicate that metadata in the data warehouse is essential for endusers?
Query templates
Navigation paths
Hardware/software of source systems
BOTH A and B
19. For performing data extraction/transformation/loading functions in the data warehouse, which of the following types of questions are answered by metadata?
I. How to improve query performance?
II. How to determine external sources?
III. Where to cleanse the data?
IV. How to switch to new data transformation techniques?
V. How to apply ongoing changes in source systems?
I, II, III, IV
I, II, III, V
I, III, IV, V
II, III, IV, V
20. Which of the following is NOT a characteristic of the Decision Trees technique of data mining?
Applies to classification and prediction
Always each lowest level branch ends up in a classification of the input record
Each node has a rule to split the subsets flowing through the branches
Suitable to trace back decision paths to ascertain reasons for the flow
21. While comparing OLAP and Data Mining which of the following represents the right matching of the technology and an example of questions answered?
I. OLAP Who are the top 100 customers for the last 3 years? Data Mining Which top 100 customers offer the best profit potential?
II. OLAP Which salespersons exceeded their quota during last 3 quarters? Data Mining Which salespersons are likely to exceed their quota next year?
III. OLAP Which customers switched to other phone companies last year? Data Mining Which customers are likely to switch next year?
IV. OLAP Which customers are likely to be bad risks? Data Mining Which customers defaulted on their mortgages last two years?
V. OLAP Last year, which stores exceeded the prior year sales? Data Mining For next two years which stores are likely to have best performances?
I, II, III, IV
II, III, IV, V
I, II, IV, V
I, II, III, V
22. Which of the following represent the major steps in the knowledge discovery process of data mining?
I. Run queries in interactive analysis sessions
II.Preprocess data
III. Mine data
IV. Select promising patterns from output
V. Apply results to create actionable items in the business
I, II, III, IV
II, III, IV, V
I, II, IV, V
I, II, III, V
23. Which of the following is the correct matching of tables and attributes in the dimensional data model for automaker sales?
Fact table Single Brand Flag
CUSTOMER dimension table Income Range
PRODUCT dimension table Day of Week
DEALER dimension table Interest Rate
24. A dimension table in a dimensional data model is generally said to be wide because it contains large number of rows of data.
True
False
25. Which of the following relates to a factless fact table in the dimensional data model?
Has no attributes apart from the primary key
Has a combination of metrics and dimensions as attributes
Serves as another fact table in addition to the regular fact table
Has miscellaneous dimensions as attributes
26. Which of the following are guidelines for consideration of applying changes to dimension tables in a dimensional data model?
I. Most dimensions are generally constant over time
II. Even those dimension attribute values that change, they change slowly
III. Overwriting of dimension attribute values is not always appropriate
IV. Applying changes to dimension attribute values is exactly similar to how changes are made in source OLTP systems
V. Applying changes to dimension attribute values depends on what must be preserved in the data warehouse
I, II, III, IV
II, III, IV, V
I, III, IV, V
I, II, III, V
27. In a dimensional data model, the options for handling "junk" dimensions, such as flags and texts are the following EXCEPT:
Place the "junk" dimensions, unchanged, in the fact table
Make each "junk" dimension into a separate dimension table
Discarding others and keep all the meaningful "junk" dimensions in a single dimension table
Exclude and discard all "junk" dimensions from the data model
28. SALESPERSON dimension table in a dimensional data model has the attribute values Old Region Name: (null), Current Region Name: North East, Effective Date: January 1, 2011. A type 3 change is applied on January 1, 2012 to change the region to MidWest. Which of the following represents the attribute values after this type 3 change is applied?
Old Region Name: North East, Current Region Name: MidWest, Effective Date: January 1, 2012
Old Region Name: (null), Current Region Name: MidWest, Effective Date: January 1, 2012
Old Region Name: (null), Current Region Name: North East, Effective Date: January 1, 2012
Old Region Name: North East, Current Region Name: MidWest, Effective Date: January 1, 2011
29. The CUSTOMER dimension table in the dimensional data model for a nationwide telecommunication company has nearly a million rows. This is a rapidly changing dimension with this dimension table having some attributes changing frequently and others slowly.
Which of the following techniques is appropriate for applying changes to the CUSTOMER dimension table?
Apply the changes as corrections without preserving history
Apply the changes as type 2 changes
Break off the rapidly changing attributes into another dimension table
Have regular downtime for the data warehouse to apply the changes
30. In the OLAP system of a data warehouse, the results of a query are displayed as follows: Rows Months; Columns Products; Pages Stores. Which of the following represents the display after one sliceanddice (rotation) operation?
Rows Products; Columns Months
Rows Stores; Columns Products
Rows Months; Columns Stores
NONE OF THE ABOVE
31. In the OLAP system of the data warehouse, which of the following does NOT refer to the feature known as transparency?
Provide true open system approach
Allow sparse matrix handling
Hide details of diverse nature of source data
Avoid exposure of users to the complexities of underlying data repository
32. In an OLAP system, the multidimensional data model for a department store has the SALES fact table and the following dimension tables: STORE, PRODUCT, TIME, PROMOTION, and CUSTOMERDEMOGRAPHICS. If you represent this as an MDS (multidimensional domain structure), you will have a
fivedimensional MDS with a total of five vertical lines.
True
False
33. The multidimensional database of an OLAP system has the following sales data: STORE: Ohio; PRODUCT: Shirt; MONTH: March; Sale Units: 250. Then, the sale units may be represented by a physical cube whose edges parallel to the X, Y, and Z axis represent the particular store (Ohio), the specific product (Shirt), and the corresponding sale month (March).
True
False
34. In a managed query environment at the data warehouse, aggregate awareness refers to which of the following?
Parsing incoming queries and recasting them to work more efficiently
Presenting results of a query in multiple formats
Making complexity of query formulation transparent to users
Ability to redirect queries to summary tables for faster retrieval
35. In the data warehouse environment, the user has equal control over getting information through preformatted reports and obtaining information through queries he or she can formulate.
True
False
36. With regard to skilled analysts (users classified as explorers), which of the following is a consideration for information delivery to them from the data warehouse?
Availability of large data volumes to analyze and mine
Support for long analysis sessions
Ability to format simple reports
Ability to produce customer invoices
37. In a Webenabled data warehouse, which of the following refers to important information derivable from clickstream data for identifying and retaining ecommerce customers?
I. Mental condition of the customer
II. Affinity between products likely to be bought together
III.Referring partner links
IV.Site navigation resulting in sales or otherwise
V.Customer demographics
I, II, III, IV
II, III, IV, V
I, II, IV, V
I, II, III, V
38. A Webenabled data warehouse can have no downtime; it is expected to be up and available all the time. This is a major implementation consideration.
True
False
39. In a Webenabled data warehouse, communication with users takes place only through HTML or XML pages.
True
False
40. In a Webenabled data warehouse, because of its wide openness, basic architectural coherence among the distributed units is achieved by adopting dimensional modeling as the basic data modeling technique.
True
False