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1. Business intelligence is a framework that allows a business to transform data into information, information into knowledge, and knowledge into wisdom.
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2. Business intelligence (BI) architecture is composed of data, people, processes, technology, and the management of such components.
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3. A data store is used by data analysts to create queries that access the database.
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4. Master data management’s main goal is to provide a partial and segmented definition of all data within an organization
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5. Operational data and decision support data serve the same purpose.
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6. Decision support data are a snapshot of the operational data at a given point in time.
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7. Queries against operational data typically are broad in scope and high in complexity.
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8. Data warehouse data are organized and summarized by table, such as CUSTOMER and ADDRESS.
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9. Relational data warehouses use multidimensional data schema support to handle multidimensional data.
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10. The data warehouse development life cycle differs from classical systems development.
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11. A data warehouse designer must define common business dimensions that will be used by a data analyst to narrow a search, group information, or describe attributes.
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12. By default, the fact table’s primary key is always formed by combining the superkeys pointing to the
Dimension tables to which they are related.
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13. Normalizing fact tables improves data access performance and saves data storage space.
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14. Periodicity, usually expressed as current year only, previous years, or all years, provides information about the time span of the data stored in a table.
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15. Multidimensional data analysis techniques include advanced computational functions.
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16. Advanced OLAP feature become more useful when access to them is kept simple.
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17. To provide better performance, some OLAP systems merge data warehouse and data mart approaches by storing small extracts of the data warehouse at end-user workstations.
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18. A star schema is designed to optimize data query operations rather than data update operations.
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19. ROLAP and MOLAP vendors are working toward the integration of their respective solutions within a unified decision support framework.
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20. The ROLLUP extension is used with the GROUP BY clause to generate aggregates by the listed columns, including the last one.
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21. The CUBE extension enable you to get a grand total for each column listed in the expression
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22. A is optimized for decision support and is generally represented by a data warehouse or a data mart.
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a. data store
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b. ETL tool
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c. data visualization
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d. data analysis tool
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23. are in charge of presenting data to the end user in a variety of ways.
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24. _____ provide a unified, single point of entry for information Distribution.
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25. In business intelligence framework, data are captured from a production system and placed in the____ on a near real- time basis.
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26. Tools focus on the strategic and tactical use of information.
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27. Which of the following is a personal analytics vendor for BI applications?
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a. IBM
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b. Kognitio
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c. Netezza
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d. MicroStrategy
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28. From a data analyst’s point of view, decision support data differ from operational data in three main areas: time span, granularity, and .
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29. Operational data are commonly stored in many tables, and the stored data represent information about a given
only.
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a. transaction
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b. database
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c. table
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d. concept
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30. The schema must support complex (non-normalized) data representations.
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a. snowflake
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b. online analytical processing
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c. decision support database
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d. multidimensional database
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31. Data implies that all business entities, data elements, data characteristics, and business metrics are described in the same way throughout the enterprise.
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a. visualization
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b. analytics
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c. mining
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d. integration
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can serve as a test vehicle for companies exploring the potential benefits of data warehouses.
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a. Data networks
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b. Data marts
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c. Data cubes
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d. OLAPs
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33. Bill Inmon and Chuck Kelley created a set of 12 rules to define a(n) .
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a. data warehouse
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b. multidimensional cube
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c. OLAP tool
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d. star schema
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34. The basic star schema has four components: facts, , attributes, and attribute hierarchies.
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a. keys
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b. relationships
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c. cubes
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d. dimensions
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35. Computed or derived facts, at run time, are sometimes called to differentiate them from stored facts.
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a. schemas
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b. attributes
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c. metrics
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d. dimensions
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36. In a star schema, attributes are often used to search, filter, or classify .
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a. tables
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b. sales
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c. facts
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d. dimensions
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37. The attribute hierarchy provides a top-down data organization that is used for two main purposes:_____ and
drill-down/roll-up data analysis.
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a. decomposition
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b. de-normalization
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c. normalization
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d. aggregation
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38. In star schema representation, a fact table is related to each dimension table in a relationship.
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a. many-to-one (M:1)
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b. many-to-many (M:M)
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c. one-to many (1:M)
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d. one-to-one (1:1)
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39. Fact and dimension tables are related by keys.
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a. shared
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b. primary
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c. foreign
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d. linked
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40. In a typical star schema, each dimension record is related to thousands of records.
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a. attribute
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b. fact
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c. key
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d. primary
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41. A schema is a type of star schema in which dimension tables can have their own dimension tables.
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a. snowflake
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b. starflake
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c. dimension
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d. matrix
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42. _____ splits a table into subsets of rows or columns and places the subsets close to the client computer to improve data access time.
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a. Normalization
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b. Meta modeling
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c. Replication
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d. Partitioning
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43. The reliance on as the design methodology for relational databases is seen as a stumbling block to its use in OLAP systems.
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44. Decision support data tend to be non-normalized, , and pre-aggregated.
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a. unique
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b. duplicated
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c. optimized
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d. sorted
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45. extends SQL so that it can differentiate between access requirements for data warehouse data and operational data.
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a. ROLAP
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b. OLAP
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c. DBMS
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d. BI
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46. A index is based on 0 and 1 bits to represent a given condition.
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a. logical
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b. multidimensional
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c. normal
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d. bitmapped
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47. Conceptually, MDBMS end users visualize the stored data as a three-dimensional cube known as a .
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a. multi-cube
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b. database cube
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c. data cube
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d. hyper cube
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48. A multidimensional database management systems (MDBMS) uses proprietary techniques to store data in
n-dimensional arrays
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a. table-like
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b. matrix-like
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c. network-like
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d. cube-like
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49. A _____ is a dynamic table that not only contains the SQL query command to generate the rows, but also stores the actual rows.
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a. SQL view
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b. materialized view
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c. star schema
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d. data cube