FIT5094 Lecture Notes - Lecture 10: Bounded Rationality, Enterprise System, Data Warehouse
2 Jul 2018
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Business Intelligence systems v/s Transaction processing systems:
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
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)
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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.
