Information Processes and Technology

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Analysing and decision support

Outcomes

This material addresses aspects of the following syllabus outcomes:

A student:

H1.1 applies and explains an understanding of the nature and function of information technologies to a specific practical situation
H1.2 explains and justifies the way in which information systems relate to information processes in a specific context
H2.1 analyses and describes a system in terms of the information processes involved
H4.1 proposes and justifies ways in which information systems will meet emerging needs
H7.1 implements and explains effective management techniques

Source: Board of studies NSW, Stage 6 Information Processes and Technology, Preliminary and HSC Courses 2007.

Analysing in a DSS is the interpretation of the data. It involves examining the data and giving it meaning.

Online Analytical Processing (OLAP) is an approach to quickly provide answers to analytical queries. OLAP also includes relational reporting and data mining. The typical applications of OLAP are in business reporting for sales, marketing, management reporting, business process management (BPM), budgeting and forecasting, financial reporting and similar areas. Databases configured for OLAP employ a multidimensional data model, allowing for complex queries. They use aspects of navigational and hierarchical databases that are faster than a relational structure.

Drilling down or up is a specific analytical technique whereby the user navigates among levels of data ranging from the most summarised (up) to the most detailed (down). The drilling paths may be defined by the hierarchies within dimensions or other relationships that may be dynamic within or between dimensions. End user applications that can request slices from OLAP servers and provide two dimensional or multi dimensional displays, user modifications, selections, ranking, calculations, etc., for visualisation and navigation purposes. OLAP clients may be as simple as a spreadsheet program retrieving a slice for further work by a spreadsheet- literate user or as high-functioned as a financial modeling or sales analysis application.