Smart New Choices for Oracle Data Mining (part 2)

By: Tim Vlamis
October 21, 2013

Data visualization is near and dear to my heart (as it is for the majority of folks engaged in advanced analytics). The new Graph node in Oracle Data Miner, the GUI extension in SQL Developer 4.0 for, adds important visualization capabilities directly in the workflow interface where analysts graphically build data mining workflows. This allows analysts to output a standard graph or chart at any point in the workflow.

Once again, simplicity and efficiency guided the Oracle product management development team in terms of deciding what capabilities to add to the interface. The choices for chart types cover the fundamental options for visualizing data including: Line Chart, Bar Chart, Scatter Plot, Histogram, and Box Plot. While this is no means a comprehensive list, it does allow for an analyst to make a chart in a manner of minutes (the interface is clean and simple and again demonstrates a “utilitarian” emphasis on achieving fast results rather than a bloated interface with every bell and whistle requiring extensive time learning the interface. The inclusion of the Box Plot graph which visually shows the distribution of data within a set is particularly welcome.

Let’s say, for example, that you are doing a clustering analysis and discover an interesting correlation among two of the parameters that is important in creating your cluster definitions and you want to highlight it directly in a graph. Sure, you could use the built-in explore capabilities for the clusters which have their own graphing features (perhaps how you discovered it in the first place), but there is all kinds of other information included in those graphs and short of taking a screen shot, it would be hard to export it. You can simply attach an apply and your original data source node to your cluster node (remember, you need a data flow node to create an export table or graph) and create a simple scatterplot that highlights the relationship (graph the two important attributes on the X and Y axes and group by cluster number) in a matter of just a few minutes. This graph can then be exported or copied to the clipboard (and it can remain in the workflow and be updated just as any other object would be.)

While there were already some very powerful visualization capabilities built in to the Explore Data node and within each of the Model Nodes themselves, this new Graph node further extends Oracle Data Miner capabilities to be a powerful, everyday tool for in-database data mining. Furthermore, it completely lives up to Oracle Data Mining’s strategic vision of extending ODM with powerful, smart capabilities that focus on delivering value quickly rather than including every knob and dial under the sun.


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