Aggregate Data Type

About Aggregate Dataype

What is aggregate data vs individual data?

Individual data is information collected from one person and tends to be very accurate but also very expensive to collect. Aggregate data is information compiled from numerous individuals from a population and tends to be less accurate but also less expensive to collect.

What is an example of aggregate data?

Aggregate data is data collected and then compiled to form a report from many individuals within a population. An example of such data might be statistical information a school presents on aggregate data on enrollment and graduation.

What Is Aggregate Data?

The definition of aggregate data is a collection of information from multiple individuals that is summarized into an official data report. The data is collected from individuals with a shared commonality, like geographical location, association with an organization, or something else of interest. What is aggregate data used for, and what does aggregate data mean for those that compile aggregate data? The purpose is to collect data on as many individuals as possible, so statistical analysis of the data can make predictions, estimate trends, assess policies, and find average values for some factor within the population of interest.

The major difference between aggregate data and individual data is its scope. Individual data involves information collected from a single individual. Aggregate data collects and combines information obtained from numerous individuals. Individual data also tends to be more accurate and costly, whereas aggregate data tends to be less accurate but more affordable. Due to privacy reasons, individual-level identifiers in aggregate data are stripped away to preserve anonymity.

Why Custom Types / Data Aggregation?

Interfaces become easier to use correctly
*   semantic data grouping: point, date, ...
*   avoids many function parameters and thus, confusion

*   can return multiple values from function with one dedicated type instead of multiple 
non-const reference output parameters
Without: Horrible Interfaces!

void closest_point_on_line (double lx2, double ly1, double lx2i, double ly2, double px,
 double py, double& cpx, double& cpy) { ... }
*   many parameters of same type --> easy to write bugs
*   non-const reference output parameters --> error-prone
*   internal representation of a line is also baked into the interface

With: A Lot Better!

struct point { double x; double y; };
struct line  { point a; point b; };
point closest_point_on_line (line const& l, point const& p) { ... }
*   straight-forward interface
*   easy to use correctly
*   If internal representation of line changes
 (e.g., point + direction instead of 2 points) --> implementation of closest_point_on_line needs to be changed too,
  but its interface can stay the same --> most of calling code doesn't need to change!
  

Aggregate Initialization
Type { arg1, arg2, ..., argN }
*   brace-enclosed list of member values
*   in order of member declaration
enum class month {jan = 1, feb = 2,..., dec = 12};
struct date {
  int yyyy;
  month mm;
  int dd;
};
int main () {
  date today {2020, month::mar, 15};    
  date tomorrow = {2020, month::mar, 16};   
}

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