FIT5195 Study Guide - Midterm Guide: 18 Months, Pragmatism, Financial Institution
2 Jul 2018
School
Department
Course
Professor
FIT5195_BUSINESS INTELLIGENCE AND DATA WAREHOUSE
1) One of the themes of the unit, as stated at the start of the semester, was to establish the
argument that business intelligence and data warehousing systems are different to other
kinds of IT systems for organisations. In what ways are these systems different?
The early focus of relational databases was on online transactional processing (OLTP), designed to
support the daily business operation requirements. The operational systems were typically
optimized for fast inserting and updating of data. As companies expanded the applications they
supported and consequently, the data stored, attention turned to providing user access for
reporting and decision support. However, a different architecture was needed where transactional
data from operational systems could be extracted, transformed, integrated, and stored to support
the reporting requirements. The DW utility was defined by four necessary components:
Subject-oriented,
Integrated,
Non-volatile,
and Time-variant.
The DW is designed to collect disparate data from operational systems and uniquely store that data
to allow end-users ready access for subsequent analysis.
A DW is intended to provide integrated data from operational systems organized for reporting,
whereas BI is intended to provide actionable information. BI can be defined as “…a set of concepts
and methodologies to improve decision-making in business through use of facts and fact-based
systems.” Simply stated, BI provides the ability to transform data into usable and actionable
information for business and organization purposes. BI is an encompassing term that combines data
architectures, technical architectures, analytic tools, and methodologies. There is significant synergy
and overlap between DW and BI. While a DW is the core repository, BI requires an information
infrastructure to provide actionable insight to decision-makers. The synergy between BI and DW has
caused them to be viewed as one entity. There are many evidences - industry reports that notes
“BI/DW is a strategic initiative that has the potential to deliver significant insights unavailable
through other means”.
There are three key aspects of BI/DW systems that make them different to other information
systems:
The task supported
The users
The development process required
1
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DIFFERENT NATURE OF THE TASK SUPPORTED – DECISION MAKING
(supports not a predictable, well-defined set of tasks, rather the complex, human-centred
process of decision making)
Decision making lays the foundation for all deliberate human action, and humans are notoriously
bad at it. People often make decisions that are irrational because of the following:
Bounded rationality: Limited memory, cognitive processing abilities, time and
resources constraints etc.
Cognitive biases: Systemic errors in judgement.
Personal preference: Same decision task leads to different outcomes for different
people.
Also, there is no single right way to make a decision. The process is inherently ambiguous, especially
for strategic decisions. Moreover, compared to a typical transaction processing system, where a
business workflow is clearly defined, developing a requirements specification for the information
system design, BI systems are capable of dealing with much more complex and ambiguously defined
tasks.
DIFFERENT, DISCRETIONARY AND POWERFUL USERS
BI/DW systems enables data and present it to the users as dashboards, reports and in other
graphical forms addressing the various business concerns of different users, such as, knowledge
workers, managers, executives, directors etc. It caters to the varying needs of these users from time
to time, providing business insight for both repetitive tasks and unique one-off tasks. This flexibility
of BI/DW systems in supporting the discretionary needs of different users makes it organisationally
powerful and better than other information systems.
DIFFERENT, CHAOTIC DEVELOPMENT PROCESS
BI/DW follows an evolutionary and adaptive approach unlike the traditional approach to SDLC. It
provides ‘intelligent’ information centred around time-variant data. It is built to help users
understand the ‘chaotic’ decision problem(s) so that they can make better decision.
2
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2) Why should BI/DW systems be developed using an evolutionary development
methodology? Describe an example of a BI or DW methodology discussed during the
semester that addresses the need for evolutionary development effectively, and how it
does so.
3
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Document Summary
The early focus of relational databases was on online transactional processing (oltp), designed to support the daily business operation requirements. The operational systems were typically optimized for fast inserting and updating of data. As companies expanded the applications they supported and consequently, the data stored, attention turned to providing user access for reporting and decision support. However, a different architecture was needed where transactional data from operational systems could be extracted, transformed, integrated, and stored to support the reporting requirements. The dw utility was defined by four necessary components: The dw is designed to collect disparate data from operational systems and uniquely store that data to allow end-users ready access for subsequent analysis. A dw is intended to provide integrated data from operational systems organized for reporting, whereas bi is intended to provide actionable information. Bi is an encompassing term that combines data architectures, technical architectures, analytic tools, and methodologies. There is significant synergy and overlap between dw and bi.
