Fun with Data Visualization Cloud–creating a timeline for album releases image 12

Fun with Data Visualization Cloud–creating a timeline for album releases

I have played a little with Oracle’s Data Visualization cloud and it is really fun to be able to so quickly turn raw data into nice and sometimes meaningful visuals. I do not pretend I grasp the full potential of Data Viz CS, but I can show you some simple steps to quickly create something good looking and potentially really useful.

My very first steps were documented in this earlier article: https://technology.amis.nl/2017/09/10/hey-mum-i-am-a-citizen-data-scientist-with-oracle-data-visualization-cloud-and-you-can-be-one-too/.

In this article, I start with two tables in a cloud database – with the data we used for the Soaring through the Clouds demo at Oracle OpenWorld 2017:

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As described in the earlier article, I have created a database connection to this DBaaS instance and I have created data sources for these two tables.

Now I am ready to create a new project:

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I select the data sources to use in this project:

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And on the prepare tab I make sure that the connection between the Data Sources is defined correctly (with Proposed Acts adding fact – lookup data – to the Albums):

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On the Visualize tab, I drag the Release Date to the main pane.

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I then select Timeline as visualization :

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Next, I bring the title of the album to the Details section:

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and the genre of the album to the Color area:

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Then I realize I would like to have the concatenation of Artist Name and Album Title in the details section. However, I cannot add two attributes to that area. What I can do instead is create a Calculation:

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Next I can use this caclculation for the details:

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I can use Trellis Rows to create a Timeline per value of the selected attribute, in this case the artist:

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It is very easy to add filters – that can be manipulated by end users in presentation mode to filter on data relevant to them. Simply drag attributes to the filter section at the top:

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Then select the desired filter values:

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and the visualization is updated accordingly:

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One Response

  1. Olaf Heimburger October 6, 2017