Test
CHAPTER 13: BUSINESS INTELLIGENCE AND DATA WAREHOUSES
Preguntas del test (49)
11. 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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22. Business intelligence (BI) architecture is composed of data, people, processes, technology, and the management of such components.
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33. A data store is used by data analysts to create queries that access the database.
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44. Master data management’s main goal is to provide a partial and segmented definition of all data within an organization
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55. Operational data and decision support data serve the same purpose.
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66. Decision support data are a snapshot of the operational data at a given point in time.
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77. Queries against operational data typically are broad in scope and high in complexity.
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88. Data warehouse data are organized and summarized by table, such as CUSTOMER and ADDRESS.
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99. Relational data warehouses use multidimensional data schema support to handle multidimensional data.
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1010. The data warehouse development life cycle differs from classical systems development.
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1111. 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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1212. 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.- AVerdadero
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1313. Normalizing fact tables improves data access performance and saves data storage space.
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1414. 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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1515. Multidimensional data analysis techniques include advanced computational functions.
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1616. Advanced OLAP feature become more useful when access to them is kept simple.
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1717. 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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1818. A star schema is designed to optimize data query operations rather than data update operations.
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1919. ROLAP and MOLAP vendors are working toward the integration of their respective solutions within a unified decision support framework.
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2020. 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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2121. The CUBE extension enable you to get a grand total for each column listed in the expression
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2222. A is optimized for decision support and is generally represented by a data warehouse or a data mart.
- Aa. data store
- Bb. ETL tool
- Cc. data visualization
- Dd. data analysis tool
2323. are in charge of presenting data to the end user in a variety of ways.
- Aa. Data stores
- Bb. ETL tools
- Cc. Data visualization tools
- Dd. Data analysis tools
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24. _____ provide a unified, single point of entry for information Distribution.- Aa. Decision support systems
- Bb. Portals
- Cc. Data warehouses
- Dd. Dashboards
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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.- Aa. decision support system
- Bb. portal
- Cc. data warehouse
- Dd. dashboard
2626. Tools focus on the strategic and tactical use of information.
- Aa. Business
- Bb. Relational database management
- Cc. Business intelligence
- Dd. Networking
2727. Which of the following is a personal analytics vendor for BI applications?
- Aa. IBM
- Bb. Kognitio
- Cc. Netezza
- Dd. MicroStrategy
2828. From a data analyst’s point of view, decision support data differ from operational data in three main areas: time span, granularity, and .
- Aa. usability
- Bb. dimensionality
- Cc. transaction processing
- Dd. sparsity
2929. Operational data are commonly stored in many tables, and the stored data represent information about a given
only.- Aa. transaction
- Bb. database
- Cc. table
- Dd. concept
3030. The schema must support complex (non-normalized) data representations.
- Aa. snowflake
- Bb. online analytical processing
- Cc. decision support database
- Dd. multidimensional database
3131. Data implies that all business entities, data elements, data characteristics, and business metrics are described in the same way throughout the enterprise.
- Aa. visualization
- Bb. analytics
- Cc. mining
- Dd. integration
32 can serve as a test vehicle for companies exploring the potential benefits of data warehouses.
- Aa. Data networks
- Bb. Data marts
- Cc. Data cubes
- Dd. OLAPs
3333. Bill Inmon and Chuck Kelley created a set of 12 rules to define a(n) .
- Aa. data warehouse
- Bb. multidimensional cube
- Cc. OLAP tool
- Dd. star schema
3434. The basic star schema has four components: facts, , attributes, and attribute hierarchies.
- Aa. keys
- Bb. relationships
- Cc. cubes
- Dd. dimensions
3535. Computed or derived facts, at run time, are sometimes called to differentiate them from stored facts.
- Aa. schemas
- Bb. attributes
- Cc. metrics
- Dd. dimensions
3636. In a star schema, attributes are often used to search, filter, or classify .
- Aa. tables
- Bb. sales
- Cc. facts
- Dd. dimensions
3737. The attribute hierarchy provides a top-down data organization that is used for two main purposes:_____ and
drill-down/roll-up data analysis.- Aa. decomposition
- Bb. de-normalization
- Cc. normalization
- Dd. aggregation
3838. In star schema representation, a fact table is related to each dimension table in a relationship.
- Aa. many-to-one (M:1)
- Bb. many-to-many (M:M)
- Cc. one-to many (1:M)
- Dd. one-to-one (1:1)
3939. Fact and dimension tables are related by keys.
- Aa. shared
- Bb. primary
- Cc. foreign
- Dd. linked
4040. In a typical star schema, each dimension record is related to thousands of records.
- Aa. attribute
- Bb. fact
- Cc. key
- Dd. primary
4141. A schema is a type of star schema in which dimension tables can have their own dimension tables.
- Aa. snowflake
- Bb. starflake
- Cc. dimension
- Dd. matrix
4242. _____ splits a table into subsets of rows or columns and places the subsets close to the client computer to improve data access time.
- Aa. Normalization
- Bb. Meta modeling
- Cc. Replication
- Dd. Partitioning
4343. The reliance on as the design methodology for relational databases is seen as a stumbling block to its use in OLAP systems.
- Aa. normalization
- Bb. denormalization
- Cc. star schema
- Dd. multidimensional schema
4444. Decision support data tend to be non-normalized, , and pre-aggregated.
- Aa. unique
- Bb. duplicated
- Cc. optimized
- Dd. sorted
4545. extends SQL so that it can differentiate between access requirements for data warehouse data and operational data.
- Aa. ROLAP
- Bb. OLAP
- Cc. DBMS
- Dd. BI
4646. A index is based on 0 and 1 bits to represent a given condition.
- Aa. logical
- Bb. multidimensional
- Cc. normal
- Dd. bitmapped
4747. Conceptually, MDBMS end users visualize the stored data as a three-dimensional cube known as a .
- Aa. multi-cube
- Bb. database cube
- Cc. data cube
- Dd. hyper cube
4848. A multidimensional database management systems (MDBMS) uses proprietary techniques to store data in
n-dimensional arrays- Aa. table-like
- Bb. matrix-like
- Cc. network-like
- Dd. cube-like
4949. A _____ is a dynamic table that not only contains the SQL query command to generate the rows, but also stores the actual rows.
- Aa. SQL view
- Bb. materialized view
- Cc. star schema
- Dd. data cube
Información
- Descripción
- CIS 3365 Test sobre CHAPTER 13: BUSINESS INTELLIGENCE AND DATA WAREHOUSES, creado por Miguel Lucero el 06/04/2017.
- Autor
- Miguel Lucero
- Idioma
- English
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- 734
- Historial
- Creado el 6 abr 2017 · actualizado el 6 abr 2017
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