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Chapter 8

BUS 237 Chapter Notes - Chapter 8: Cluster Analysis, Decision-Making, Olap Cube

Business Administration
Course Code
BUS 237
Zorana Svedic

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For business managers, decision making or choosing from a range of alternatives is
the essence of management.
Decision making process is much more complicated for three reasons:
The concept of rationality is hard to define
Good outcomes may occasionally result from irrational processes, and bad
outcomes can result from good processes
Humans intend to be rational, but there are limits on our cognitive capabilities.
This is called bounded rationality.
Herbert Simon suggested that we must satisfice, that is, choose the most
reasonable and available solution rather than the perfect choice.
Management Misinformation systems:
This theory suggested that designers of MIS make several erroneous assumptions about
managerial decision making. Theorized by Russell Ackoff.
1. The first assumption is that managers will have no problem making decisions if they
get data they need. Ackoff countered that for most managers, too many possibilities
exist; they should not expect to make better decisions even with perfect data. The
uncertainty and complexity surrounding decisions make them challenging.
2. A second assumption is that poor decisions are made because managers lack
relevant information. On the contrary, Ackoff argued, managers suffer more from an
overabundance of irrelevant data. Today, we refer to this overabundance as
information overload.
3. A third erroneous assumption is that managers know what data they need. Ackoff
argued that in reality, managers are often not sure what data they do require. And
because they are unsure, the tendency is to ask for as much data as they can get,
thus promoting information overload.
Today, managers face information overload
Digital universe is doubling in size every two years
Data is growing at the rate of 40 percent a year
Occurs inside and outside of organizations
The challenge is to find the appropriate data and incorporate them into their
decision-making processes
It is hard enough to make decisions when you have good-quality data. However, it is even
harder when you have poor-quality data.
Data from operational systems can be processed to create basic reports with few issues.
Raw operational data are seldom suitable for more sophisticated reporting or data mining.
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First the data may be problematic or what is termed as dirty data. For example,
using value B for customer gender, etc.
Missing values are a second problem.
Inconsistent data is the third problem, which is particularly common in data that has
been gathered over time.
Data not integrated is the fourth problem. It can occur if the data resides in different
sources or are incompatible with the intended purpose.
Data can also be too coarse or too fine. Data granularity refers to the degree of
summarization or detail. Coarse data are highly summarized; fine data expresses
details that are too precise. Exaple: It is possile to apture the ustoer’s likig
behaviour in what is termed as clickstream data. But this data is too fine, very
detailed, and may get overwhelming, and so is discarded. Generally, it is better to
have granularity that is too fine, than too coarse. If the granularity is too fine, the
data can be made coarser by summing and combining. Google Analytics is a good
example of summing and combining data.
WHAT ARE OLTP; and How Does It Support Decision Making?
Using computers to capture information electronically is often referred to as being
online. Most web-based applications are examples of online systems.
If you are collecting data electronically, and processing the transactions online, then
you are using an online transaction processing (OLTP) system.
OLTP systems - backbone of all functional, cross-functional, and inter-organizational
systems in an organization
They are designed to efficiently enter, process, and store data. OLTP systems
combine large databases with efficient input devices, to process transactions quickly
and accurately.
OLTP systems support decision making by providing the raw information about
transactions and status for an organization
There are 2 basic ways in which transactions can be processed:
Real-time processing
Transactions are entered and processed immediately upon entry, then the
system is operating in real time because there is little or no delay in updating the
system with new data.
Examples: airline reservation systems, banking systems
Batch processing
System waits until it has a batch of transactions before the data are processed
and the information is updated
Example: transfer of all daily branch transactions to the central office for
The choice of whether to use real-time processing or batch processing depends on the
nature of the transactions, the cost of the system, and the needs of the organization.
Real-time systems tend to be more complex and cost more to implement. However,
real-time systems provide the most up-to-date information, and that is often important.
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