Month: November 2016

Why can’t I move my visualization?

The Title Bar must be visible [on] to rearrange a visualization within the same page or to move the visualization to another tab. The Title Bar is what is used to grab the visualization using the left mouse button. There are several ways to activate the Title Bar.

By default, when creating a new visualization, the Title Bar is on. However, often we use a Spotfire Template or someone else’s project or simply forgot we set the Title Bar off. Activating the Title Bar is different depending if we have a Text Area versus a Table or Graphical Visualization. In the figure below the Title Bar is on for the Pie Chart but off for the Text Area, see highlighted areas. Note, mouse must be moved to these areas to see if Title Bar is on or off.

To turn on the Title Bar in the Text Area we right mouse click in the Text Area > Properties > check “Show title bar.” If we wanted to add / remove Title Bar in a Table or Graphical visualization, we right mouse click in white space next to our graphical visualization (or inside Table visualization) > Properties > Visualization Features > check “Title Bar,” as in second figure below.

Finally, the Title Bar can be activated from any visualization under Properties > General.

Paul is a geoscientist specializing in data analytics and visualizing a lot of data in a small amount of space. As Edward Tufte says, “There is no such thing as data overload, just a failure of design.”

About Default Marking Settings in Spotfire

Green is the default marking color in Spotfire that marks Table and Cross Table visualizations only. The marking color is applied automatically to the Table visualization when selecting a data range in either the Table visualization or another visualization type. In the example below, we have selected the Mid Range data bar in the Bar Chart using the left mouse button which simultaneously marks the Table visualization.

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Paul is a geoscientist specializing in data analytics and visualizing a lot of data in a small amount of space. As Edward Tufte says, “There is no such thing as data overload, just a failure of design.”

Want to use Amazon S3 for your Spotfire Library? Read this first.

I’m not one for clickbait so my apologies to the esoteric group this pertains to. The quick and dirty of it is that you can’t use TIBCO’s ./ tool for connecting the library to an external source like Amazon S3. Ordinarily the code is this:

$ ./ config-library-external-s3-storage –bucket-name=MYBUCKET –access-key=MYACCESSKEY –secret-key=MYSECRET

This won’t work. Spotfire Server will try to connect and give you something like:

Connecting to the library…OK

Retrieving items from database…OK

Retrieving items from external storage…Unable to execute HTTP request: rai-exchangeai.s3-us-west

Is that a malformed URL for an Amazon S3 API call? You bet. Open up your configuration.xml and fancy your own URL by changing the region value to Spotfire doesn’t include an example in the installation guide so this is my gift to you.

Technical Director at

Spark lines can show the shape of highly variable data in a small amount of space

In Spotfire Graphical Table visualization, the use of sparklines is a fantastic way to quickly visualize our data in table format. But, what if we have highly variable data in which it would be better to use a logarithmic scale on the Y-axes? Note, there is no option for using a logarithmic scale on the spark line axes visualizations. We have two options here: to use multiple scales or write a custom expression with multiple scales.

One of the main uses of sparklines is to show the “shape” of our data. If our data range is less variable, then a single arithmetic scale for all sparkline axes is fine. However, in the case below we need to use a different arithmetic scale for each spark line in the column to honor the high variability of the data.

Go to Properties of Graphical Table > Axes and select spark line column as seen below. Now select Settings button for that spark line column.

Then, select Axes and change radio button under “Y-axis scale” from “One scale for all sparklines in this column” to “Multiple scales.” We do the same for all spark line columns with highly variable data we want to “compare,” as seen in the second spark line column in the Graphical Table below.

Note the huge improvement in being able to see the “shape” of our data with “Multiple scales” selected, compared to the first visualization above.

Next, if we want a Log or Logarithmic scale, we can easily write a custom expression as seen below by right mouse clicking of Y-axis name in Sparkline Settings.

Insert Log function Custom Expression, then hit Okay.

Compare final Log Scale Graphical Table below to previous two arithmetic Tables above. Note visualization below has “Multiple scales.”

Finally, if we use “One scale for all sparklines in this column” instead of “Multiple scales” the results may not show enough differentiation especially if you have extreme outliers. Compare this last log image with our first arithmetic one.

Paul is a geoscientist specializing in data analytics and visualizing a lot of data in a small amount of space. As Edward Tufte says, “There is no such thing as data overload, just a failure of design.”

Spotfire Functions – Lines & Curves – Line from Column Values

  • Have you struggled to add type curves to visualizations?
  • Would you like to add lines to a plot and be able to change the format?
  • Have you tried to use Line from Column Values before and gotten a jumbled mess?

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Guest Spotfire blogger residing in Whitefish, MT.  Working for SM Energy’s Advanced Analytics and Emerging Technology team!

Addendum to Azure Install of Spotfire Server

Microsoft Azure doesn’t let you switch databases: “USE statement is not supported to switch between databases. Use a new connection to connect to a different database.” The USE command is used in the create_databases scripts in the beginning of the installation. This is a known bug for Azure, take note here:

Your best bet is to do the following:

  • Add -dspotfire_server to the populate and create_user sqlcmds
  • Comment out the USE commands and connect directly.

Good luck!

Technical Director at