ITM 320 - Chapter 1, True and False
BI represents a bold new paradigm in which the company's business strategy must be aligned to its business intelligence analysis initiatives.
False
Business intelligence (BI) is a specific term that describes architectures and tools only.
False
Computerized support is only used for organizational decisions that are responses to external pressures, not for taking advantage of opportunities.
False
Data generators are a precursor, and is not included in the analytics ecosystem.
False
Decision support system (DSS) and management information system (MIS) have precise definitions agreed to by practitioners.
False
Demands for instant, on-demand access to dispersed information decrease as firms successfully integrate BI into their operations.
False
Due to industry consolidation, the analytics ecosystem consists of only a handful of players across several functional areas.
False
Information systems that support transactions as ATM withdrawals, bank deposits, and cash register scans at the grocery store respect transaction processing, a critical branch of the FBI.
False
Managing information on operations, customers, internal procedures and employee interactions is the field of cognitive science.
False
Many commercial business intelligence (BI) products were well established in the 1970s.
False
Successful BI is a tool for the information systems department, but is not exposed to the larger organization.
False
The growth of hardware, software, and network capacities has had little impact on modern BI innovations.
False
The use of dashboards and data visualizations is seldom effective at identifying issues in organizations, as represented by the Silvaris Corporation Case Study.
False
Computer applications have moved from transaction processing and monitoring activities to problem analysis and solution applications.
True
During the early days of analytics, data was often obtained from the domain experts using manual processes to build mathematical or knowledge-based models.
True
In the 2000s, the DW-driven DSSs began to be called BI systems.
True
Managing data warehouses requires special methods, including parallel computing and/or Hadoop/Spark.
True
Many business users in the 1980s referred to their mainframes as "the black hole," because all the information went into it, but little ever came back and ad hoc real-time querying was virtually impossible.
True
The use of statistics in baseball by the Oakland Athletics, as described in the Moneyball case study, is an example of the effectiveness of prescriptive analytics.
True
Traditional BI systems use a large volume of static data that has been extracted, cleansed, and loaded into a data warehouse to produce reports and analyses.
True
