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Leverage the 'Attribute' Function to Boost Data Insights

Philippe Lions
Senior Director

Sometimes you have to change the parameters of what you are looking at to gain a better perspective of what you want to see.

Take the story of the invention of Velcro. A Swiss engineer by the name of George de Mestral was hunting with his dog when he noticed how some of the weeds would attach to the dog's fur. Whereas we might just pull the burrs out and move on, de Mestral saw the literal connection between the two surfaces. He eventually recreated the design into what we know as Velcro today.

In building data visualizations, it's important to determine the relationships between two or more data points: distance as it relates to rate and time… points attempted over points achieved… profit vs. loss, etc. For example, you may need to count how many orders each customer has placed and using distinct values as attribute to aggregate revenue by.

In Oracle Data Visualization and Oracle Business Intelligence platforms, there are default values that allow for quick publishing and insight. But what if your values are not listed or don't stack up the way you want?

Both Oracle Data Visualization and Oracle Business Intelligence platforms include an 'attribute' function. This allows you to treat any aggregated metric value into an attribute discrete member. Calculated metric values can thus be used as series for any visualizations, like a bar graph.

If you ever used the 'treat as an attribute' flag in the Answers expression editor, the attribute function is the syntax behind this functionality. It's accessible in any calculations available in Data Visualization or Oracle Business Intelligence Enterprise Edition.

An example of the value that this capability brings, is when one needs to compute aggregates on rows that are grouped by values of another metric aggregate: How much revenue is contributed annually by all customers that only buy once from us, twice, thrice, etc. cohorts?

The explicit syntax for this function is:  

ATTRIBUTE(<expression> BY <attribute list> WHERE <predicate>)  

The BY clause may be empty, in which case grand total grain is assumed.

The recording below shows how to leverage the Attribute feature. In no time at all, you will be able to master your visualization values and manage your data in new ways.


Of course, seeing is believing. If you like what you see and you want to try it for yourself, visit www.oracle.com/goto/datavisualization to learn more about Oracle Data Visualization and get your free trial.


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