Hey Mum, I am a Citizen Data Scientist with Oracle Data Visualization Cloud (and you can be one too)

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One of the Oracle Public Cloud Services I have seen mouthwatering demos with but have not actually tried out myself is Oracle Data Visualization Cloud. I had several triggers to at last give it a try – and I am glad I did. In this article a brief report of my first experiences with this cloud service that aims to provide the business user – aka citizen data scientist – with the means that explore data and come up with insights and meaningful visualizations that can easily be shared across the team, department or enterprise.

I got myself a 30-day trial to the cloud service, uploaded a simple Excel document with a publicly available dataset on the countries of the world and started to play around. It turned out to be quite simple – and a lot of fun – to come up with some interesting findings and visualizations. No technical skills required – certainly not any beyond an average Excel user.

Steps:

  • get a trial account – it took about 5 hours from my initial request for a trial to the moment the trial was confirmed and the service had been provisioned
  • enter the Data Viz CS and add a new Data Source (from the Excel file with country data)
  • do a little data preparation (assign attributes to be used as measures) on the data source
  • create a new project; try out Smart Insights for initial data exploration, to get a feel for attributes
  • create some visualizations – get a feel for the data and for what DVCS can do ; many different types of visualizations, various options for filtering, embellishing, highlighting; many dimensions to be included in a visualization
  • try a narrative – a dossier with multiple visualizations, to tell my story

In a few hours, you get a very good feel for what can be done.

 

Create Countries as my new data source

First steps: download countries.csv from https://www.laenderdaten.info/downloads/  . Create Excel workbook from this data. Note: I first tried to upload the raw csv file format, but that ended with an internal error.

 

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The data that was imported is shown. Now is a good moment to set the record straight – any meta data defined at this point is inherited in projects and visualizations that use this data. For example: if we want to calculate with attributes and use them as values – for the size of bubbles and stacks and to plot a line – we have to identify those attributes as measures.

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Once the data source is set up – we can create our first project based on that data source by simply clicking on it. Note: the PROPOSED_ACTS and ACT_ALBUMS data sources are based on database table in an Oracle DBaaS instance to which I have first created a connection (simply with host, port, service name and username & password).

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My First Project – Data Preparation & Initial Exploration

Here is the Data Preparation page in the project. We can review the data, see what is there, modify the definition of attributes, prescribe a certain treatment (conversion) of data, add (derived) attributes etc.

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If we click on the Visuals icon in the upper right hand corner, we get a first stab at visualization of some of the data in this data source. Out of the box – just based on how DVCS interprets the data and the various attributes:

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For example the number of countries per continent. Note how we can select different measures from the dropdownlist – for example area:

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This tells us that Asia is the largest continent in landmass, followed by Africa, Russia is the largest country and the size of all countries using a currency called Dollar put together is the largest, with Rubel using countries (probably just one) as a runner up. Note: all of this – out of the box. I am 10 minutes into my exploration of DVCS!

 

First Visualizations – Let’s try a Few Things

Go to the second tab – Visualize.

Drag an attribute – or multiple attributes – to the canvas.

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The default visualization is a pivot table that presents the data for the selected attribute. Drag two more attributes to the canvas:

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The result is a matrix of data – with the measure (area) in the cells:

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In order to prepare the visualization for presentation and sharing, we can do several things – such as removing columns or rows of data that is not relevant, setting a color to highlight a cell:

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Define range filters on selected attributes – for example filter on countries with at least a 45M population or

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When the filter has been set, the matrix adapts:

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We can try out different styles of visualization – what about a map?

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DVCS recognizes the names of continents and countries as geographical indications and can represent them on a map, using color for total area. Let’s remove continent from the Category dimensions, and let’s set bubble size for population:

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If we are interested in population density, we can add a calculated value:

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Some more examples:

Select countries by size per continent – in a horizontal stack chart:

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and a treemap – with population added in as additional attribute represented through color:

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Any visualization we like and want to include in our final narrative can be saved as an insight:

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On the Narrate tab – we can include these insights in a meaningful order to tell our story through the data visualizations. Also see Building Stories.

 

Resources

Oracle Data Visualization Cloud Service: https://cloud.oracle.com/en_US/data-visualization  (at $75.00 / Named User / Month with a minimum of 5 users a fairly friendly priced offering)

The country data is downloaded from https://www.laenderdaten.info/downloads/

Documentation on Oracle Data Visualization Cloud Service: http://docs.oracle.com/en/cloud/paas/data-visualization-cloud/bidvc/getting-started-oracle-data-visualization.html 

Documentation on Building Stories: http://docs.oracle.com/en/cloud/paas/data-visualization-cloud/bidvc/building-stories.html#GUID-9D6282AA-C7B7-4F7E-9B9E-873EF8F1FB5D

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About Author

Lucas Jellema, active in IT (and with Oracle) since 1994. Oracle ACE Director and Oracle Developer Champion. Solution architect and developer on diverse areas including SQL, JavaScript, Docker, Machine Learning, Java, SOA and microservices, events in various shapes and forms and many other things. Author of the Oracle Press books: Oracle SOA Suite 11g Handbook and Oracle SOA Suite 12c Handbook. Frequent presenter on community events and conferences such as JavaOne, Oracle Code and Oracle OpenWorld.

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