The activity of summarizing and consolidating records is often called "aggregation" in the technical vocabulary of database experts. Aggregation simply means that data is grouped and summarized by subjecting the data to some mathematical operation. The results is a summary of the data at a higher level.
Consider a simple illustration. Suppose a company scanned into its database every transaction, including the date, price, item, and amount of purchase and location. To determine which item sold the most in 2000 would require grouping each item by category and summing their total.
Analysis depends on consolidating data through mathematical operations that reveal meaningful relationships.
The aggregate view can be described as a higher level view of your data. The data you see at a higher level summarizes and consolidates data from a lower level. Of course, Interactive Reporting enables you to break down or de-aggregate the data into its component parts. You can see that aggregation involves summarizing data by performing some mathematical operation on a group of related records. For example, suppose you want to know the average value of purchases for each store in 2001.
One of the most appealing features of Interactive Reporting is the elegant simplicity of its aggregation techniques. With the simple drag-and-drop of a data item, you can reorganize your data and answer the question. Remove an item or drill-down into your data and you can de-aggregate your data.
Interactive Reporting provides a great deal of flexibility in how you choose to aggregate your data. One possibility is to aggregate your data at the time of your query. In this case, the database server actually performs the aggregation for you. Alternatively, you can aggregate data on your desktop without involving the server. There are advantages and disadvantages to each of these methods.
You pre-aggregate data as it is retrieved from the database. This approach involves aggregation as part of a query. Once the query is processed, the data arrives on your desktop in aggregate format.
When pre-aggregated in this way, similar records are consolidated and numeric data is aggregated by category.