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System Maps
A system map is a diagrammatic representation of a set of things working together. It focuses on the components
and boundaries of a system. System map helps us to find relationships between different elements of the
problem which we have scoped. It helps to find a solution to achieve the goal of our project. Let us understand
system maps with the help of an example.
Streets are safe for pedestrians to walk if the number of people driving on the roads are less.
If the number of vehicles on the road increases, the emission levels also increase.
–
– +
Driving Safe Streets Walking
+
Emissions
We use system maps to understand the complex issues that have inter-connected factors affecting each other.
A system comprises:
• Elements: These are different, discrete elements within the system.
• Interconnections: These are the relationships that connect the elements.
Rules for system maps are:
• The circles represent elements.
• Arrows are used to represent relationships/interconnections.
• The ‘+’ and ‘-’ signs are indicators of the nature of a relationship. The arrowhead depicts the direction of the
effect and the sign (+ or -) shows their relationship.
• If the arrow goes from X to Y with a + sign, it means that both are directly related to each other. That means if
X increases, Y also increases and vice versa.
• If the arrow goes from X to Y with a -sign, it means that both the elements are inversely related to each other.
That means if X increases, Y would decrease and vice versa.
After collecting accurate data, the next step is data exploration. Data exploration means to find the patterns and
trends in the data. It is the third stage in the AI project cycle and the initial step in data analysis. It is used to
understand what is in a dataset and the characteristics of the data.
Data exploration cleans the big data to provide an input to an AI project. Terabytes of data sitting in the data
centre unused is a burden, if correctly processed it can become digital gold.
AI Project Cycle 223

