Chapter 13: Business Intelligence and Data Warehouses

The data warehouse development life cycle differs from classical systems development. a. True b. False

ANSWER: True

_____ are qualifying characteristics that provide additional perspectives to a given fact.

ANSWER: Dimensions

_____ are in charge of presenting data to the end user in a variety of ways. a. Data stores b. ETL tools c. Data visualization tools d. Data analysis tools

ANSWER: c

_____ tools focus on the strategic and tactical use of information. a. Business b. Relational database management c. Business intelligence d. Networking

ANSWER: c

A _____ index is based on 0 and 1 bits to represent a given condition. a. logical b. multidimensional c. normal d. bitmapped

ANSWER: d

In a typical star schema, each dimension record is related to thousands of _____ records. a. attribute b. fact c. key d. primary

ANSWER: b

_____ can serve as a test vehicle for companies exploring the potential benefits of data warehouses. a. Data networks b. Data marts c. Data cubes d. OLAPs

ANSWER: b

_____ provide a unified, single point of entry for information distribution. a. Decision support systems b. Portals c. Data warehouses d. Dashboards

ANSWER: b

_____ functionality ranges from simple data gathering and transformation to very complex data analysis and presentation.

ANSWER: BI business intelligence

_____ is a term used to describe a comprehensive, cohesive, and integrated set of tools and processes used to capture, collect, integrate, store, and analyze data with the purpose of generating and presenting information used to support business decision making.

ANSWER: Business intelligence

_____ use web-based technologies to present key business performance indicators or information in a single integrated view, generally using graphics in a clear, concise, and easy to understand manner.

ANSWER: Dashboards

_____ means to decompose data into more atomic components or data at lower levels of aggregation.

ANSWER: Drill down

_____ are numeric measurements (values) that represent a specific business aspect or activity.

ANSWER: Facts

A data store is used by data analysts to create queries that access the database. a. True b. False

ANSWER: False

A data warehouse designer must define common business dimensions that will be used by a data analyst to expand a search. a. True b. False

ANSWER: False

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. a. True b. False

ANSWER: False

Data warehouse data are organized and summarized by table, such as CUSTOMER and ADDRESS. a. True b. False

ANSWER: False

Master data management's main goal is to provide a partial and segmented definition of all data within an organization. a. True b. False

ANSWER: False

Normalizing fact tables improves data access performance and saves data storage space. a. True b. False

ANSWER: False

Operational data and decision support data serve the same purpose. a. True b. False

ANSWER: False

Queries against operational data typically are broad in scope and high in complexity. a. True b. False

ANSWER: False

The ROLLUP extension is used with the GROUP BY clause to generate aggregates by the listed columns, including the last one. a. True b. False

ANSWER: False

______ is a method or process of government.

ANSWER: Governance

_____ are quantifiable measurements (numeric or scale based) that assess a company's effectiveness or success in reaching its strategic and operational goals.

ANSWER: Key performance indicators KPI KPIs Key performance indicators (KPI)

_____ is a collection of concepts, techniques, and processes for the proper identification, definition, and management of data elements within an organization.

ANSWER: Master data management MDM Master data management (MDM)

_____ makes a copy of a table and places it in a different location to improve access time.

ANSWER: Replication

_____ is a measurement of the density of the data held in the data cube and is computed by dividing the total number of actual values in the cube by the total number of cells in the cube.

ANSWER: Sparsity

A star schema is designed to optimize data query operations rather than data update operations. a. True b. False

ANSWER: True

Advanced OLAP feature become more useful when access to them is kept simple. a. True b. False

ANSWER: True

Business intelligence (BI) architecture is composed of data, people, processes, and technology working together to facilitate and enhance a business's management and governance. a. True b. False

ANSWER: True

Business intelligence is a framework that allows a business to transform data into information, information into knowledge, and knowledge into wisdom. a. True b. False

ANSWER: True

Decision support data is a snapshot of the operational data at a given point in time. a. True b. False

ANSWER: True

Multidimensional data analysis techniques include advanced computational functions. a. True b. False

ANSWER: True

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. a. True b. False

ANSWER: True

ROLAP and MOLAP vendors are working toward the integration of their respective solutions within a unified decision support framework. a. True b. False

ANSWER: True

Relational data warehouses use the star schema design technique to handle multidimensional data. a. True b. False

ANSWER: True

The CUBE extension enables you to get a subtotal for each column listed in the expression, in addition to a grand total for the last column listed. a. True b. False

ANSWER: True

To support a(n) _____ adequately, the DBMS might be required to support advanced storage technologies, and even more importantly, to support multiple-processor technologies, such as a symmetric multiprocessor (SMP) or a massively parallel processor (MPP).

ANSWER: VLDB very large database very large database (VLDB)

A _____ schema is a type of star schema in which dimension tables can have their own dimension tables. a. snowflake b. starflake c. dimension d. matrix

ANSWER: a

A(n) _____ is optimized for decision support and is generally represented by a data warehouse or a data mart. a. data store b. ETL tool c. data visualization d. data analysis tool

ANSWER: a

Bill Inmon and Chuck Kelley created a set of 12 rules to define a(n) _____. a. data warehouse b. multidimensional cube c. OLAP tool d. star schema

ANSWER: a

Data visualization has its roots in the _____ sciences, which focus on how the human brain receives, interprets, organizes, and processes information. a. cognitive b. developmental c. social d. health

ANSWER: a

In star schema representation, a fact table is related to each dimension table in a _____ relationship. a. many-to-one (M:1) b. many-to-many (M:M) c. one-to many (1:M) d. one-to-one (1:1)

ANSWER: a

Operational data are commonly stored in many tables, and the stored data represents information about a given _____ only. a. transaction b. database c. table d. concept

ANSWER: a

The reliance on _____ as the design methodology for relational databases is seen as a stumbling block to its use in OLAP systems. a. normalization b. denormalization c. star schema d. multidimensional schema

ANSWER: a

_____ extends SQL so that it can differentiate between access requirements for data warehouse data and operational data. a. ROLAP b. OLAP c. DBMS d. BI

ANSWER: a

To deliver efficient decision support, OLAP tools must have advanced data _____ features.

ANSWER: access

The _____ hierarchy provides a top-down data organization that is used for two main purposes: aggregation and drill-down/roll-up data analysis.

ANSWER: attribute

48. A _____ is a dynamic table that not only contains the SQL query command to generate the rows, but also stores the actual rows. a. SQL view b. materialized view c. star schema d. data cube

ANSWER: b

An multidimensional database management systems (MDBMS) uses proprietary techniques to store data in _____ n-dimensional arrays. a. table-like b. matrix-like c. network-like d. cube-like

ANSWER: b

Decision support data tends to be non-normalized, _____, and pre-aggregated. a. unique b. duplicated c. optimized d. sorted

ANSWER: b

From a data analyst's point of view, decision support data differ from operational data in three main areas: time span, granularity, and _____. a. usability b. dimensionality c. transaction processing d. sparsity

ANSWER: b

Computed or derived facts, at run time, are sometimes called _____ to differentiate them from stored facts. a. schemas b. attributes c. metrics d. dimensions

ANSWER: c

Conceptually, MDBMS end users visualize the stored data as a three-dimensional cube known as a _____. a. multi-cube b. database cube c. data cube d. hyper cube

ANSWER: c

Fact and dimension tables are related by _____ keys. a. shared b. primary c. foreign d. linked

ANSWER: c

In a star schema, attributes are often used to search, filter, or classify _____. a. tables b. sales c. facts d. dimensions

ANSWER: c

In business intelligence framework, data are captured from a production system and placed in _____ on a near real-time basis. a. decision support system b. portal c. data warehouse d. dashboard

ANSWER: c

The _____ schema must support complex (non-normalized) data representations. a. snowflake b. online analytical processing c. decision support database d. multidimensional database

ANSWER: c

Data _____ implies that all business entities, data elements, data characteristics, and business metrics are described in the same way throughout the enterprise. a. visualization b. analytics c. mining d. integration

ANSWER: d

The attribute hierarchy provides a top-down data organization that is used for two main purposes: _____ and drill-down/roll-up data analysis. a. decomposition b. de-normalization c. normalization d. aggregation

ANSWER: d

The basic star schema has four components: facts, _____, attributes, and attribute hierarchies. a. keys b. relationships c. cubes d. dimensions

ANSWER: d

Which of the following is a personal analytics vendor for BI applications? a. IBM b. Kognitio c. Netezza d. MicroStrategy

ANSWER: d

Which type of data describes numeric facts or measures that can be can be counted, ordered, and aggregated? a. qualitative b. ordinal c. nominal d. quantitative

ANSWER: d

_____ splits a table into subsets of rows or columns and places the subsets close to the client computer to improve data access time. a. Normalization b. Meta modeling c. Replication d. Partitioning

ANSWER: d

A(n)_____ is a read-only database optimized for data analysis and query processing.

ANSWER: data warehouse

A data _____ is a small, single-subject data warehouse subset that provides decision support to a small group of people.

ANSWER: mart

Data _____ tools are tools that provide advanced statistical analysis to uncover problems and opportunities hidden within business data.

ANSWER: mining

The most distinctive characteristic of modern OLAP tools is their capacity for _____ analysis.

ANSWER: multidimensional

In multidimensional terms, the ability to focus on slices of the cube to perform a more detailed analysis is known as _____.

ANSWER: slice and dice

A data _____ is a centralized, consolidated database that integrates data derived from the entire organization and from multiple sources with diverse formats.

ANSWER: warehouse