Comparative Tiled Growth Rate : immediate deep insight on your data using Oracle DV Templates

Oracle Analytics Cloud offers the ability to apply an existing analysis on any other dataset, different from the one it was built on. This feature is called Replace Data Set. By leveraging this capability, one can re-use any existing project to gain insight on virtually any dataset. Pre-defined Projects can be used as templates for anyone to gain deep insights on their own datasets.

In this post, let's see how to leverage the DV Growth Binning example available on Oracle Analytics Library (https://www.oracle.com/analytics-library).

What is the DV Growth Binning example project ?

The Growth Binning example originally uses a dataset about Countries Ecological Footprints. The data shows 50 years of history on an aggregated carbon footprint metric for 176 countries over the world. The DV calculations help grouping these countries into 5 equal groups (quintiles), according to the growth rate of each countries on that metric over 50 years. First group shows slowest growing countries (countrieds that showed decrease in their carbon footprints over years this case), last group showing the top fast growing countries.

The DV project then shows a few more details of which individuals make-up each group, in two different canvases : Details and List. List, in particular, is a page showing all the individuals sorted by their growth rates but also indicating the gross value of the metric. That allows to immediately recognize individuals that have significant contribution in value, and high or low growth rate.

The project delivers this insight for year-based, quarter-based or month-based analysis, to accomodate for datasets that have different time-spans or grain. All of the calculations are run-time project calculations, no Data Flow is needed.

How to apply this insight to my own dataset ?

This project can be used as template on any other dataset, as long as a date and a metric exist in the dataset. This is done by simply using the Replace Dataset feature, the process is very simple and takes just a few seconds. This brief video shows a recording of applying the project to various datasets :

By leveraging the Dataset Replace feature, every project can become a template that anyone can re-use on various datasets, within seconds, like in this example. This empowers Oracle DV users to get to deep insights extermely quickly on any datsets.

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Un-documented Beta OAC 18.3.3 Feature : Configuring Synonyms for ASK Interface

The ASK interface in with OAC is a very simple and direct way to gain insight about your data in seconds. Just type (or pronounce) phrasal questions, OAC will interpret your question, match it with most likely measures and attributes exist in any indexed dataset you have access to, and return visualizations that best meet your question. Simple and efficient, this works both in the web based OAC UI and via the mobile interface in Day by Day Application.

OAC 18.3.3 (Sept 2018) introduced several enhancements to ASK, like better interpretation of questions constructs, understanding of Top/Bottom question syntaxes, etc. But one feature only made it as Beta in 18.3.3 because a robust finalized UI was still lacking : configuring Synonyms for column name indexes. This feature did not make it into documentation, but is already operational in 18.3.3 pods.

The configuration of synonyms using the beta feature is simple and quick, but quite manual and fragile. File syntax and dataset names are to be strictly respected. This short video briefly describes it.

The feature will be greatly enhanced in upcoming releases of OAC both for the experience, the UI and the capability. The current status of it may not migrate automatically when the feature is fully released. 

But in the meantime it can help address some immediate needs today. Like for example rudimentary translation of system defined column names in different languages so users get to ask simple questions in their native tongue, and get answers from a single source in ASK.

Are you an Oracle Analytics customer or user?

We want to hear your story!

Please voice your experience and provide feedback with a quick product review for Oracle Analytics Cloud!