Data assets can be regarded as one version of business “gold”.
For example, your list of customers is a very valuable data asset. If that list were to go missing or the data were to be corrupted, you would not have people to service, and your ability to make an income would be hurt.
Data assets can be broken into the following families
- Units (vacancies)
Inside of these families there lives more data assets. For example, properties is a “container” for
- Street address information
- Deeds information (such as purchase price, property extent)
- Debt funding information
- Property category
- Sub-category to property category
- Property attributes such as size, floors, aircon types, solar power etc.
- Owner information
- The list goes on
In CRE these data assets talk to each other. For example, a property, is owned by a business, and this business has contacts to talk to on the property. Further, this property is tenanted by one or more businesses, each of whom has contacts.
Thus commercial property professionals are required to nimbly deal with and navigate through enormously complicated data structures.