Use Oracle Data Visualization Desktop to present information and insights.
If, like me, you still remember some of the stories you read when you were a child, it’s probably the twists and turns, the cliff-hangers, the unanswered questions, and the final resolution that make those stories so memorable. As adults, we still enjoy stories, and good ones resonate both intellectually and emotionally with an audience. Stories aren’t limited to fiction, of course, and using Oracle Data Visualization Desktop and some data of interest, you can visualize that data, uncover insights, and then use the tool’s storytelling features to make that data more meaningful when you present it to others.
In this article, I’ll use Oracle Data Visualization Desktop and its visualization and storytelling features to explore, understand, and then tell the story about my attempt to lose some weight by exercising more. I recorded my workouts and weight each day, using wearable devices and a smartphone app. You can download and unzip the sample datafiles used in this article and download Oracle Data Visualization Desktop if you want to try the article example yourself. Or you can use your own fitness tracker or workout app data to build your own story by exporting the data to Microsoft Excel XLSX files and using Oracle Data Visualization Desktop.
Let’s start by taking a spreadsheet datafile exported from a cycling workout smartphone app. It contains a record of every cycling workout I recorded over a nine-month period starting in January 2016. I’ll upload the file into Oracle Data Visualization Desktop; review it; and, if necessary, change how columns within it are designated as either measures or attributes and configure the outside temperature measure to aggregate by averaging its values (rather than adding them all together).
Now I can create my first data visualization that will show how the distance logged for the workouts I recorded with the smartphone app varied over the nine months of data. Because the workout app also recorded the outside temperature when the workout took place, I’ll then overlay that information onto the visualization to see whether how hot or cold it was outside affected the distance logged for a workout.
In reality, even though the trend in the workout distance may have fallen, the overall distance logged per month actually rose, due to these additional but shorter workouts. To show this, I first need to create a new calculated column for the month each workout was logged and then use that new column to show the distance traveled per month.
So it looks as if my overall workout distance has increased over time, but has this extra exercise resulted in weight loss being recorded in my other smartphone health app, or was all of that working out a wasted effort on my part? To find out, I’ll now add the second datasource containing weight readings over the same period and see whether this increased exercise activity has helped me shed those extra holiday pounds.
Save this as another insight by clicking the insights icon on the left-hand menu panel, clicking Add Insight, and naming this insight And Exercise Seems to Have Worked!
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This example created and explored visualizations using the data from two datasources. I saved data of interest as insights so I could come back to them later. Insights are snapshots of data visualizations at a point in time and can be refreshed to show updated data if necessary. Insights can also be used to tell a story about the data that can be more effective than just a set of saved reports in a catalog.
To view and optionally edit the sequence of insights that make up the story for this data set, click the Story Navigator button in the application toolbar to show the insights in the order you created them. Use the back and forward buttons to view the story timeline, and edit or remove insights from the story timeline to create the final story presentation, as shown in Figure 7.
Figure 7: Data visualization with story navigator
Finally, if you want to present these insights and the story they tell about the data to friends or colleagues, you can switch the application to presentation mode by clicking the Presentation Mode button in the same application toolbar to remove all the menus and buttons and focus just on the story and the data.
Data, and the meaning behind it, resonates better with audiences and is remembered longer when you use storytelling techniques and effective visualizations to present your insights to others. Oracle Data Visualization Desktop puts these capabilities into the hands of anyone with a recent desktop PC and some data of interest. Try this storytelling approach out yourself, and see what stories you can tell with your data.
Mark Rittman is an Oracle ACE Director and independent analyst who has been working with Oracle Business Intelligence and big data technology for more than 15 years.