Continuous attributes are one of the new features available in GrapeCity ActiveAnalysis. In a nutshell, they allow you to convert your numeric and date-based attributes into a continuous line.
This is hard to explain with a concise statement, so let’s take an example: Say you are examining sales by date.
If you are looking at the date attributes in a discrete manner (that is, the way that Data Dynamics Analysis currently works) then you see each individual year, quarter, month, day, etc. as a separate column in the pivot grid.
To continue our example, let’s say we’re looking at the sales in July. We’ll find a column for each day with the sales totals under each column. We see many of these columns, each individually labeled. Fortunately for us, they’re in order so we can use a line graph to compare each cell to the ones next to it. However, there are 31 days in July so we have 31 columns and unless your monitor is 40″ wide you probably can’t see all of that.
This is where a continuous attribute steps in. With numeric and date-based attributes, there is an established order to the attributes and you could fit them to a number line, or in our case, an axis. That is what we do with a continuous attribute: rather than display each date or numeric value by itself, we plot the values on a graph axis.
With the date-based data now condensed into an axis, we no longer have to dedicate 15-20 pixels of screen real estate to every single date. After all, you and I both know that July 2nd follows July 1st.
Notice that it also shows something that our discrete view didn’t show. It shows us that there is a gap in our data. If you look carefully at the first screenshot again, you’ll see that the gap was there all along, but we previously had no easy way of seeing it. Unfortunately, the screenshot tool didn’t capture the mouse cursor, so it’s hard to tell, but the gap in the data is for July 4, 2010, a day in which no sales took place.
This feature is available to use with any attribute where we have access to the raw date or number value. If you are using a relational data source, this is almost always the case, however in SQL Server Analysis Services we don’t necessarily have access to that data. It is all dependent on whether the attribute’s ValueColumn is set properly.