The data parts used within the current context were mainly categorized as follows: number of employees, type of industry, available off street parking spaces, and location.
This was a brief and initial data set with the aim to extend more to it in order to allow for more accurate decision support; however this is enough data to give a context or base of implementation.
The reasoning behind number of employees stems from the fact that as a business grows through the course of time, if more employees join, then it is a potential indication that the business has thrived and is progressing.
The type of industry is considered because in certain situations, having a parking space nearby helps but in others it does not.
The available parking spaces (off street) is considered as people value having a parking space near their employment location. Having this is important as high talent employees would want to be happy in their work space and not have to worry about these matters.
Location was also considered because some businesses thrive in certain locations while others don’t.
The end result was a data gathering exercise highlighting where employees have been high. With the current data set, there is not enough to suggest that this is proof of business success but may indicate a potential.
As the product evolves, there will be more automation introduced and more accurate and predictive result sets may be produced.