business firm as system
TRANSCRIPT
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Business
Environment
and the AIS
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The Business Firm as a System
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System Characteristics of
Business FirmsObjectives
Environment
Constraints
Input-Process-Output
Feedback
ControlsSubsystems
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Major Subsystems
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1. Organizational Structure
It shows how the tasks are divided, groupedand coordinated. An organizational chart is a
diagram that depicts an organbizationalstructure.
Major Subsystems
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2. Information SystemThe information system can be depicted
as a group of related subsystems, such as the
production information system, theaccounting information system, and themarketing information system.
Major Subsystems
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3. Operational Sytem
The operational system of a firm is thecollection of primary physical processes.
Major Subsystems
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The Operational
System of aManufacturing Firm
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Facilities
Labor(humanservices)
Data
Funds
AcquiringMaterials
ProducingFinishedGoods
StoringFinishedGoods
ShippingFinishedGoods
Goodsto
Customer
SupportingOperations
AIS
Information
Funds
MaterialfromSupplier
Manufacturing Firm
Data and information flow
Physical flows
The Operational System of aManufacturing Firm
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Organizational
Structures
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Matrix Structure It blends functional and project oriented
structures.
Organizational Structures
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Decentralized StructureA considerable degree of authority is
delegated to middle-level and lower levelmanagers within the structures.
Organizational Structures
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Network Structure It represents an interconnected but non-
hierarchal structure that is both flexible andfluid.
Organizational Structures
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Operational System
An operational system is a term used in datawarehousing to refer to a system that is used toprocess the day-to-day transactions of an
organization. These systems are designed soprocessing of day-to-day transactions isperformed efficiently and the integrity of thetransactional data is preserved.
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Operational Systems vs. Data
Warehousing
The fundamental difference betweenoperational systems and data warehousing
systems is that operational systems aredesigned to support transactionprocessing whereas data warehousing systemsare designed to support online analytical
processing(orOLAP, for short).
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Based on this fundamental difference,datausage patterns associated with operationalsystems are significantly different than usage
patterns associated with data warehousingsystems. As a result, data warehousing systemsare designed and optimized usingmethodologies that drastically differ from that
of operational systems.
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Operational Systems Data Warehousing Systems
Operational systems are
generally designed to support
high-volume transaction
processing with minimal back-
end reporting.
Data warehousing systems are generally designed to
support high-volume analytical processing (i.e. OLAP)
and subsequent, often elaboratereport generation.
Operational systems are
generallyprocess-
orientedorprocess-driven,
meaning that they are focused
on specific business processes
or tasks. Example tasks include
billing, registration, etc.
Data warehousing systems are generally subject-
oriented, organized around business areas that the
organization needs information about. Such subject
areas are usually populated with data from one or
more operational systems. As an example, revenue
may be a subject area of a data warehouse that
incorporates data from operational systems that
contain student tuition data, alumni gift data,
financial aid data, etc.
Comparison
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Operational Systems Data Warehousing Systems
Operational systems are
generally concerned
with current data.
Data warehousing systems are generally concerned
with historical data.
Data within operational
systems are
generally updated
regularlyaccording to need.
Data within a data warehouse is generally non-volatile,
meaning that new data may be added regularly, but onceloaded, the data is rarely changed, thus preserving an
ever-growing history of information. In short, data within
a data warehouse is generally read-only.
Operational systems are
generally optimized to
performfast inserts and
updates of relatively small
volumes of data.
Data warehousing systems are generally optimized to
performfast retrievals of relatively large volumes of data.
Comparison
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Operational
Systems
Data Warehousing Systems
Operational systems are
generally application-
specific, resulting in a
multitude of partially or
non-integrated systems
andredundant data (e.g.
billing data is not integrated
with payroll data).
Data warehousing systems are generally integratedat a
layer above the application layer, avoiding data
redundancy problems.
Operational systems
generally require a non-trivial level of computing
skills amongst the end-user
community.
Data warehousing systems generally appeal to an end-user community with a wide range of computing skills,
from novice to expert users.
Comparison