Flashcards in 12 IPT - DSS Deck (14):
Identify the key structural components of an expert system.
- Inference engine
- Database of facts
- Knowledge base
- User interface
Identify the two types of inference engines.
- Backwards chaining
- Forwards chaining
Outline an advantage and a disadvantage of using macros in spreadsheets.
- Participants can use a single keystroke, command or key shortcut to run a predefined series of commands. Thus, saving time.
- If any step in a macro is incorrect, it may not be noticed and may be difficult to fix. This can lead to inaccuracies in data.
Define the term data mining and explain its use in data warehousing.
Data mining is a process used by corporations/individuals to aid in decision making. This requires a program to analyse through the data in data warehouses to detect trends.
Data warehouses: A series of databases that work together to store data and detect interpretable patterns.
Define the acronym OLAP and outline its use.
OLAP stands for On-line analytical processing and is used to visualise data collected by companies or individuals. This visualisation is then used to define present and predict future trends.
Outline four issues relating to decision support and decision support systems.
- Preserving an expert’s knowledge
- Improving performance and
consistency in decision-making
- Rapid decisions
- Ability to analyse unstructured
Outline two advantages and disadvantages of using graphs to represent data.
Graphs allow for visual representation and a clearer comparison between the trends or forms of data. This also aids visual workers. However, graphs can be misinterpreted and may be time consuming to create depending on the technology available.
Identify two types of graphs and what they would measure.
Types of graphs include:
- Column - Amounts
- Pie - Percentages
- Line - Variable vs time
- Venn diagram - Comparitive data
- Radar chart - Comparative measurements
Briefly define GDSS (Group Decision Support System)
A Group Decision Support System (GDSS) is an interactive, computer-based system that helps a team of decision-makers solve problems and make choices.
Define "Data Warehouse"
A data warehouse stores data from various datasets such as OLTPs, CRMs (Client Relation Management Systems), and ERPs (Enterprise Resource Planning Systems). The data from these various sources then goes through an ETL process (Extraction, Transformed and Loaded) where they are stored into the data warehouse.
Data warehouses are also "historical" and "non-editable". Data from the data warehouse can then be analysed using OLAPs, data mining and data visualisation.
What are the reasons for a DSS?
1) Preserving an expert's knowledge: e.g. where experts aren't readily available or there is a high turnover in the company
2) Improving performance and consistency in decision-making: e.g. approving loans, no longer rely on people's biases, using a DSS the decision needs to be made based on strict rules
3) Rapid decisions: DSS as a tool can give answers immediately, and does not require users to wait for an expert's opinion
4) Ability to analyse unstructured situations: In unstructured situations such as flying an aeroplane through a storm, DSS can ensure the expert ("pilot") is able to make the best possible decisions
What are the responsibilities (or issues) with data mining?
1) Erroneous inference
Data mining finds patterns among a large data set. Some of these patterns may not be useful or could be in error if the data set was not large enough in number, was gained from limited or biased sources, or did not consider other causalities. e.g. People who go to private schools will do well in HSC.
Some companies such as Woolworths will have a large data set to mine. With "big data", they are able to accurately profile their customers, gaining information without consent from customers. e.g. Woolworths can profile someone from the groceries they buy (e.g. regularly baby food) and try to sell them health insurance for infants.
Issues to DSS
responsibility for decisions made using
decision support systems
If a pilot received erroneous data from their DSS system which results in a plane crash, it could be legally difficult to determine who was responsible. The pilot, the makers of the DSS or the expert who provided the knowledge base to the DSS.