It could be multiple tables from multiple sources, multiple kinds of relationships: one to one, one to many, and many to many. With other reporting tools, much of these data cannot has to be flattened, but you then lose a lot of the power of retaining the original multiple one to many, many to many relationships.
The tool can automatically roll-up data on the fly in-memory. Tables can be transformed into roll-up tables. There’s interaction across all for both charts and dashboards. We’d like to say you can select anywhere, and it updates all the charts everywhere, you’ll see that in our upcoming demo. And in-memory it gives you the speed that you need for this speed of thought analysis.
If you’re traversing a network to a database, asking a database to do work, it’s a lot slower than if the data is physically resident right there where the app is running. Also new field calculations, numerical strength, date and conditional formatting are part of these tools. The concept is you’re setting this up for visual discovery so people can visually explore things that human minds can see, patterns.
From there, they can drill down further and ask new questions. Included with this is predictive modeling. The idea here is the human mind can look at 5,10,or 15 fields and start figuring what’s going on by visually exploring data, but much of these data sets have 50 or 100 fields, and in some of cases it’s four, five hundred fields wide.
The human mind can’t visually tackle that. Predictive modeling determines mathematically what the five related fields are in the buckets. From there you see the pattern in a few minutes. But this is the concept of a visual tool and that display and analysis, discovery and analysis versus display or reporting.