Teri Patsilaras

8月 112022

If you haven't explored data with Automatic Actions enabled yet, then read on to learn about some fast and easy ways to gain insights using One-way filters, Two-way filters or Linked Selection.

Part 1 – Easy exploration for multiple data sources

In this post, we focus on One-way filters.

Here are the benefits and behaviors of using Automatic Actions: One-way filters:

  • Applied at the Page level. This means all objects on the page will be filtered if possible.
  • Same data source objects are filter automatically, different data source objects require column mappings to be defined under the global Map Data.
  • Filters are combined with the AND operator and applied in the order in which they are selected.

We will also cover some Pro Tips for when using Automatic Actions:

  • For Control Objects:
    • If you want to filter multiple data sources, use the columns from the Global Mapped Data definition for the Role assignment.
    • Use the mapped column with the highest cardinality.
  • Use the original column in visualizations and not the Custom Category used for mapping data.
  • Use Object Titles to label the data source.

Part 2 - Dive into multidimensional or hierarchical data easily

In this post, we cover Automatic Actions: Two-way filters.

The term “two-way” sounds like you get only two opportunities to select a value, but this is not the case. The first value selected will automatically filter all of the objects with either the same data source or mapped data sources on the page. Then all subsequent value selections will filter all objects on the page including the first source object with an AND condition.

This type of compound filter is especially beneficial for exploring multidimensional or hierarchical data easily. This is because the objects can display different levels of hierarchy and the filtering will simultaneously be applied and you can continue to dive into the hierarchy or dimension.

Part 3 - Find related data fast

In Part 3 of this series, I cover the Automatic Action: Linked Selection. The Linked Selection Action highlights, or “selects”, the same data simultaneously for all of the objects on the page that support manual linked selections.

The key to using Linked Selection is using related data and data items, but not the exact same Role assignments. Let SAS Visual Analytics do all the work to simultaneously highlight the selected data points. It’s important for report viewers to understand that the selected/highlighted data may represent the entire value or part of the value of the selected row, cell, data point, bubble, tile, etc.

Here are some of the key tips I will cover for Linked Selections:

  • Automatic Actions are applied at the Page level in the report.
  • All objects which support actions will be automatically included in the selected Automatic Action.
  • Map Data for different data sources. Include all of the columns you want to be linked.
  • Create Custom Categories to assist with Mapping Data for different data sources.
  • Hold the Ctrl key to select multiple values.
  • Use color meaningfully. Since objects are not filtered but values are selected/highlighted it is important to coordinate colors for data values with purpose.


Watch this video tutorial as I walk through an example of each Automatic Action type.

View more of my Communities posts.

SAS Visual Analytics: Automatic Actions: a three-part series was published on SAS Users.

3月 242021

In one of my prior posts, I discussed the power behind a Hidden Data Role in SAS Visual Analytics. In this post, I provide a summary of places you can go to learn more about other enhancements to the List Table.

The List Table can be more than just a black-and-white ledger style visual. Here is one example where I’ve highlighted some of the enhancements you can apply to the List Table:

List Table Example 1

You can also control the styling of the List Table by changing the header and total cell background colors as well as an alternating row color:

If you want to style your List Table for all users to have the same color scheme and other style enhancements, consider using either a Report Theme or Object Templates for consistency across report developers.

Want to learn more? The SAS Communities version of this article provides examples of:

  • Display Rules: Color-Mapped, Expression or Gauge
  • Abbreviated value
  • Sparkline
  • Totals
  • Freeze Columns to the left

You can also learn more about Cell Graphs by reading the article, Use SAS Visual Analytics 8.3 Cell Graphs to enhance List Tables and Crosstabs, or by checking out this video:

Get to know the List Table was published on SAS Users.

11月 112020

Data visualization has never been more widespread and consumed by a global audience as it has been this year with the Coronavirus pandemic. If you are interested in the statistics behind many of the numbers you see displayed in data visualizations then please reference my colleague’s blog series:

One visualization that is commonly used to display metrics of Coronavirus is a bar line chart where the bars display the actual values and the line is a moving average metric.

The screenshot below shows the number of web visits per week and a 5 week moving average value. I’ve named it Visits (5 Week Moving Avg Bracket) since I am including both past and present data points into this calculation.

I will demonstrate how to easily generate this moving average metric to use in your SAS Visual Analytics reports.

Bar Line With Moving Average

Moving Average

Moving average is essentially a block of data points averaged together, creating a series of averages for the data. This is commonly used with time series data to smooth out short-term fluctuations and highlight longer-term trends or cycles.

Traditionally, the moving average block takes the current data point and then moves forward in the series, which is often the case in financial applications. However, it is more common in science and engineering to take equal data points before and after the current position, creating what I am calling a moving average bracket.

SAS’ Visual Analytics calculation gives you the flexibility to define how to average the data points for your moving average: how many positions prior and/or after the current data point.

Steps to generate the Moving Average

From the Data pane, right-click on the measure you want to generate the moving average and select New calculation.

New Calculation

Next, in the Create Calculation window:

  • Name: Visits (5 Week Moving Avg Bracket) (a meaningful name of your choice)
  • Type: Moving average
  • Number of cells to average: 5 (or the number of your choice)

Click OK.

New Moving Average

Notice that you did not have the option to specify how many data points to include before and after the current position. To do that, we will right-click on the generated calculation and select Edit.

Edit Moving Average Scope

From the Edit Calculated Item window, make your starting and ending point position selections. The current position is denoted as zero. In my example, I want a 5 point moving average bracket, therefore I want to average the two positions before current, (-2), current, and then the two positions after current (2).

Aggregate Cells Average

Success. We now have generated our 5 point moving average bracket. You may be wondering, where do you specify the time frame? Granted I named this metric Visits (5 Week Moving Average Bracket) but I did not specify the week time metric anywhere. This is because, for this aggregated measure, the time duration is directly dependent on the data items you have assigned to the object.

In my example, for my web visit data, I want to look at the aggregation at the week level, therefore this Aggregate Cell measure will be grouped by week. I wanted to name my measure appropriately so that any user reading the visual knows the time frame that is being averaged.

If you are unsure of how you want to aggregate your time series, or you are allowing your report viewers the ability to change the role assignments through self-service reporting (see blog or YouTube for more information) then it would be best if you name your measure as 5 Point Moving Average Bracket and leave off the aggregation of the time series.

Bar Line Role Assignments

Let’s take a look at what the numbers are behind the scene. I’ve expanded the object to its Maximize mode so that I can see the summary table of the metrics that make up this object.

The data points will average until the full bracket size is met, then it will slide that bracket down the time series. Keep in mind that our bracket size is five points, two previous data points (-2), current data point (0), and two future data points (2).

Let’s look at week 01. Week 01 is our current, or zero, position. We do not have any prior data points so the only points that can be used from the bracket are positions 1 and 2. See the first highlighted yellow Visits (5 Week Moving Avg Bracket) and how it corresponds to the Visits.

Next, week 02 is able to include a -1 position into the bracket. The full moving average bracket isn’t met till week 03 where all of the data points: -2 through 2 are available. Then the moving average bracket slides along the rest of the time series.

Moving Average Bracket Details

Seeing the object’s summary data and the breakdown of how the moving average bracket is calculated for the data should drive home the fact that the time period aggregation is solely driven by the object’s role assignments.

In my second example, I am looking at retail data and this is aggregated to the day level.

By Day Example

I chose to demonstrate a 14 day moving average bracket.

14 Day Moving Average

Bar Line Chart

In both of my examples, I used the Dual axis bar-line chart object. Default Y axis behavior for bar charts is to start at zero, but line charts since they are intended to show trend can start at a value other than zero. Use the Options pane to select your desired line chart baseline. I choose to have both my bar and line charts fixed at zero. Explore the other Options to further customize your visual.

Bar Line Chart


Calculating the moving average is offered as a SAS Visual Analytics out-of-the-box Derived Item. See the SAS Documentation for more information about Derived Items.

Once you’ve specified the window of data points to average for the moving average you can go back and edit the starting and ending points around the current position. Remember that you will not be specifying a time frame for the aggregation but it will be dynamically determined based on the role assignments to the visual.

Learn more

If you are interested in other uses for the moving average operator Aggregate Cells take a look at this article: VA Report Example: Moving 30 Day Rolling Sum.

Also, check out these resources:

SAS Visual Analytics example: moving average was published on SAS Users.

7月 312020

In this SAS demo, I demonstrate how to prompt for a date range in a SAS Visual Analytics report. We walk through how to configure prompts using four types of control objects:

Slider (range)

Slider (single value)

Drop-down list

Text input

Then we cover how to define parameters and configure filters for report objects using the date prompted boundaries. These techniques are demonstrated using SAS Viya 3.4 SAS Visual Analytics 8.4 but can be applied to earlier releases.

I've also written accompanying articles in a four-part series. Below the video see the links to the articles and their corresponding timestamps in the video.

01:33 – 1st Example: Slider (Range) - How to prompt for a date range in a SAS VA report – Example 1 Slider (Range)

03:01 – 2nd Example: Slider (Single Value) - How to prompt for a date range in a SAS VA report – Example 2 Slider (Single Value)

14:04 – 3rd Example: Drop-down list - How to prompt for a date range in a SAS VA report – Example 3 Drop-down list

19:33 – 4th Example: Text input - How to prompt for a date range in a SAS VA report – Example 4 Text input

Other References

How to prompt for a date range in a SAS Visual Analytics Report - Four Part Series was published on SAS Users.

4月 102020

First introduced in SAS Visual Analytics 8.3, common filters are filters that can be shared between objects in your reports.

Common filter benefits include:

  • Easy to assign the same filter conditions to other report objects.
  • When you edit a common filter, it is updated everywhere that the common filter is used.
  • A common filter is available for the entire report, across pages.

Common filter limitations include:

  • Objects must share the same data source as the common filter definition.
  • Common filters are not available across multiple reports.

While the benefits speak for themselves, common filters also expedite designing reports and exploring data by quickly reusing the same filter conditions with only a few mouse clicks.

Let’s look at some examples of using common filters. In the screenshot below, I defined a filter to return data for the last 30 days. I converted that filter to a common filter and now the Last 30 Days common filter can be applied to any object in this report that uses the same data source. Then I applied it to the bottom treemap object.

In my second example, I parameterized a text input control to capture a user-defined value. Then I defined a parameter-driven filter for the bar chart object. Next, I converted that filter to a common filter named Text Input Contains Filter and applied it to the list table object below.

In my third example, I parameterized two drop-down list controls to capture date boundaries. Then I defined a parameter-driven filter for the waterfall chart object. Next, I converted that filter to a common filter named FromToWeekFilter and applied it to the key value object.

Pro tip: Embrace meaningful filter names. Recall that these common filters are associated with the data source for which they are defined. Being able to quickly identify a common filter definition by its name will save you additional mouse clicks in the long run.

Example 1: Last 30 Days Filter

Let’s pick up where we need to define the filters. Therefore, both objects have been added to the report page with roles assigned.

Next, select the line chart object and open the Filters pane. Click + New filter then select Advanced filter.

Now we will use the built-in filter conditions offered in SAS Visual Analytics. First, select the date/datetime data item, Day. Second, scroll down in the available conditions until you see Last 30 days, then double click on the condition to add it to the expression editor. Third, give the filter condition a meaningful name and as a final step, be sure the number of returned observations is expected. Click OK.

Now we need to convert this filter to a common filter. With the line chart object still selected, on the Filters pane, use the Last 30 Day overflow menu and select Change to common filter.

You should now see the Last 30 Days listed as a Common Filter in the Data pane.

Lastly, we can apply this common filter to the treemap object. Select the treemap object, then open the Filters pane. Next click + New Filter and select the common filter Last 30 Days.

It’s good practice to title your objects to reflect any filters that may be defined for them. Especially if there are no prompts, i.e. control objects, driving the subset of data. This is so your report consumers quickly understand that they are only seeing, in this case, the last 30 days of data.

Example 2: Text Input Contains Filter

This next example will define a parameter-driven common filter. If you are not familiar with using parameters in SAS Visual Analytics, start with this article and refer to the additional materials at the end.

See the screenshot below for more information on the data item role assignments for each object. The most important role that will drive the parameter-driven common filter is the parameter. The parameter, TextInputParameter, is a character parameter assigned to the text input control object and it is the only role assignment. If there is nothing entered in this prompt, i.e. control object, then the filter will return all of the data. We will define a contains expression to only return data rows that contain the entered text.

With the bar chart object selected, open the Filters pane and click + New filter and select Advanced filter.

Now we need to build our parameter-driven filter expression. In this filter we will be checking if the Product Description data item Contains the entered text stored in the TextInputParameter. I wrapped each string expression in an UpCase function so that mixed case is ignored. I could have just as easily used the LowerCase function to get the same result.

And finally, remember to give your filter a meaningful name. The returned observations number is not reflective of an applied filter since I do not have any text entered in the control object. If you had text entered there, then your returned observation number may show a subset of matched rows.

Now we need to convert this object-level filter to a common filter. With the bar chart still the active object, open the Filters pane and use the Text Input Contains Filter overflow menu and select Change to common filter.

You should now see the Text Input Contains Filter in the Data pane.

To add this common filter to the lower list table object, select the list table object and open the Filters pane. Click on the + New filter and select the Text Input Contains Filter.

Now let’s test the filter. In the screenshot below, I’ve typed the word red. Recall that our filter expression is to return rows where Product Description contains the entered text. Notice that even though I do not have the data item Product Description assigned as a data role in the bar chart object, SAS Visual Analytics is still able to apply the filter appropriately. The list table object does have a role assigned for Product Description so that filter application is easier to identify.

I used the contains operator instead of the equals to return a partial match to the Product Description to help identify trends across multiple Products. In these next examples, I entered the text (F) and (M) to return the rows where the Product Description indicates gender-specific products.

Example 3: From – To Week Filter

This last example will also define a parameter-driven common filter. If you need a more step-by-step guide to similar examples, refer to this YouTube video tutorial:

See the screenshot below for more information on the data item role assignments for each object. This example differs from the last in that these control objects, the drop-down lists, use both Category and Parameter Role assignments. The Year-Week data item will provide the available values and the selections will be stored in the parameters FromWeekParameter and ToWeekParameter. I will then create a common filter for an inclusive between of the selected year week values to apply to both the key value object and the waterfall chart.

With the waterfall chart object selected, open the Filters pane and click + New filter and select Advanced filter.

Now we need to build our parameter-driven filter expression. In this filter, I will subset the Year-Week date values which are inclusively between the FromWeekParameter and ToWeekParameter boundaries. Follow these steps:

  1. Select the date/datetime data item, Year-Week.
  2. Scroll down in the available conditions till you see Year-Week BetweenInclusive(‘x’,’y’), then double click on the condition to add it to the expression editor.
  3. Drag the FromWeekParameter and ToWeekParameter from the parameter data items list to the expression.
  4. Give the filter condition a meaningful name. Click OK.

Test the filter by adjusting the values in the drop-down list controls.

Now we need to convert this object-level filter to a common filter. With the waterfall chart still the active object, open the Filters pane and use the FromToWeekFilter overflow menu and select Change to common filter.

You should now see the FromToWeekFilter in the Data pane.

To add this common filter to the key value object; select the key value object and open the Filters pane. Click on the + New filter and select the FromToWeekFilter.


Remember that once a common filter is defined, it can be used for any object in the report that uses the same data source. In these examples, I applied the common filter on the same report page but you can use a common filter on any page within the report. Recall that all of the common filters are listed and available when I click to apply a new filter to an object.

Hopefully these examples have shown you new ways to explore data faster!

Additional materials for using parameters in SAS Visual Analytics:

Using common filters in SAS Visual Analytics was published on SAS Users.

11月 152019

Designing interactive reports can be a fun and unique challenge. As user interface experience designers can attest, there are several aspects that go into developing a successful and effective self-service tool. Granted I’m not designing the actual software, but reports require a similar approach to be sure that visualizations are clear and that users can get to the answers they are looking for. Enter prompts.

Reports prompt users to better understand trends, how their data points compare to the whole, and to narrow the scope of data. Being able to pick the placement of these prompts quickly and easily will open the possibilities of your report layouts! I’m specifically speaking about Report and Page level prompts. Traditionally, these global prompt controls were only able to be placed at the top; see the yellow highlighted areas below.

Let’s take a look at an example report with the traditional Report and Page prompt layout. The Report prompts are extremely easy to pick out, since they sit above the pages, but the Page prompts can sometimes blend in with other prompts contained in the report body.

Introduced in the SAS Visual Analytics 8.4 release is the ability to control the layout position of these prompts. Using my example report, let’s change the placement of these prompts. In Edit mode, open the Options pane and use the top level drop-down to select the report name. This will activate the report level, and the report level Options will display. Next, under the Report Controls subgroup, move the placement radio button to the west cardinal point.

Depending on the type of control objects you are using in your report, you may not like this layout yet. For instance, you can see here that my date slider is taking up too much space.

When you activate the slide control, use the Options pane to alter the Slider Direction and Layout. You can even use the Style option to change the font size. You can see that after these modifications, the Report prompt space can be configured to your liking.

Next, let’s change the placement for the Page prompts, for demonstration purposes. From the Options pane, use the top drop-down to select the page name. This will activate the page level, and the page level Options will display. Next, under the Page Controls subgroup, move the placement radio button to the west cardinal position.

You can see that the direction of the button bar control was automatically changed to vertical. Now we can clearly see which prompts belong to the page level.

If I switch to view mode, and adjust the browser size, you can get a better feel for the Report and Page prompt layout changes.

But as with many things, just because you can, doesn’t mean you should. This is where the report designer’s creativity and style can really take flight. Here is the same report, but with my preferred styling.

Notice that I kept the Report prompts along the top but moved the Page prompts to the left of the report. I also added two containers and configured a gray border for each container to better separate the objects. This helps the user quickly see that the drop-down will filter the word cloud is only. I also used the yellow highlighting through styling and a display rule to emphasize the selected continent. The bar chart is fed from an aggregated data source which is why the report prompt is not filtering out the other continents.

Feel free to send me your latest report design ideas!

Additional material related to Report and Page prompts:

New control prompt placement option in SAS Visual Analytics was published on SAS Users.

7月 252018

In SAS Visual Analytics 8.3, a Data View is a reusable and shareable template for a data source. That means that the data view is tied to the data source, and not to the report. If you update a data view it will not automatically propagate those changes into a report.
So, what can a data view do for you? Plenty! Here are just a few of the settings and customizations that a data view can save for a data source: (taken from documentation here):

  • Data item settings such as names, formats, classifications, and aggregations
  • Data source filters
  • Hierarchies
  • Derived data items
  • Calculated items
  • Custom categories
  • Duplicate data items
  • Show / hide status for data items
  • Unique row identifier selection

Create a Data View

Now you must be wondering, how do you save all these wonderful customizations for your data source? Answer: by creating a Data View.
To get started, use the Data Source menu and select Save data view…. In this example, I created a hierarchy for the SASHELP CARS data set but as you can see from the list above you could have created many more calculations, custom categories, etc.

Then give the Data View a name. A few other things you may notice about this Save Data View dialogue are the options for: Default data view and Shared data view.

Default data view

A default data view is automatically applied whenever the data source is added to the report.
Each user can create their own data view of the source data and select their own default data view. This could lead to each user having a personalized default view. But, what if you want share your data views with others on your team? Or have everyone start with the same default view? That is when you need to first be an Application Administrator and second use the Shared data view option.

Shared data view

In order to be able to share a data view, you must be an Application Administrator. Then the option to share a data view will be available. Once a data view is shared for a data source, other users with access to that data source will be able to apply that data view.

Apply a Data View

Data views are templates of saved settings, hierarchies, custom categories, calculated data item, etc. which can be combined in an infinite amount of ways. Therefore, it follows that multiple data views can be applied to the same data source. In the example above, I created a new hierarchy for the SASHELP CARS data set. But I could also create a new data view which changes the aggregation of the MPG measures to reflect the average aggregation and not the default sum aggregation.

To apply a data view: open a new report, select your data source, then use the Data Source menu and select Data views…. You will see any individually created data views as well as any shared data views. Highlight the data view you wish to apply, then select Apply. Repeat for all of the data views you wish to apply.

If any data items are duplicated with the addition of data views then, as shown below, those data items are given a (n) after their names.

Administrator-controlled Default Data View

We've learned what Data Views are and that we can share them. How can we ensure that all the users who select a data source get the same starting point with a particular data view? To set this up, you must be an Application Administrator and the Data View must be Shared.
Once these two criteria are met, you can navigate to the report's overflow menu and select Edit administration settings. Then select the data source and which data view to apply as the default for all users.

Caution: If the user has already selected a personal default data view, then the personal default data view overrides the administrator-set default data view. Remember that an individual user can apply a personal or another shared data view and override the default data view.


Data Views are just one of the exciting new features in SAS Visual Analytics 8.3. A few key points to remember:

  • Data Views are tied to a data source, not a report. If a data view is edited, those edits do not propagate to the reports that applied that Data View.
  • A data source can have multiple Data Views applied.
  • Only an Application Administrator can share a data view with other users as well as define a default data view for a data source for all users. Any personal defined default data views override the administrator-set default data view.
  • Data Views are a template of data settings and edits – not a fully robust semantic layer where updates are pushed to all instances of usage. While Data Views can be used to assist in defining commonly used calculations and custom categories, remember that each user can still create their own data views and thus override the administrator-set default.

Using Data Views in SAS Visual Analytics was published on SAS Users.

6月 012018

You will not find an object in SAS Visual Analytics named Dynamic Text. Instead, you will find a Text object that allows you to insert dynamically driven data items. By using the Text object’s dynamic capabilities you can build custom report titles, object titles, emphasize measures and even supply the last modified time of the data source in your SAS Visual Analytics Report. In this post, I will outline the ways how you can leverage the Text object’s dynamic capabilities.

In this example report below, I have used a red font color to indicate the dynamically driven text.
Dynamic Text in a SAS Visual Analytics Report

Let’s take a look the available dynamic roles in the Text object. You can see from the Objects pane that the Text object is grouped under Other.

From the Data pane we have the ability to add both Measure and Parameter data items. From the interactive editor of the Text object shown below, we also have the ability to insert the Table Modified Time and Interactive Filters.

The following sections will demonstrate how to configure each of these dynamically driven elements of the Text object.

Interactive Filters

The out of the box display for Interactive Filters includes the selected values for control objects added to either the Report or Page Prompt areas.

To edit, be sure you are in Edit mode of Explore and Visualize. Click on the Text object to make it the active window and double click inside, then the interactive editor will open. Next, click on the Interactive Filters button. Use your cursor to position where you would like to add static text. In this case, I added the qualifier Default filter information:.

Multiple control object values are separated by a comma and also accommodates multi-value control objects.


While the Interactive Filter functionality is extremely useful, you may want to use prompt values more granularly to create custom report titles or even object titles. To do this, you must first create a parameter to hold the value selected in the control object, then use that parameter in the Text object.

In my example report, I have two prompts and two custom object titles leveraging parameters. Let’s look at each one individually.

First is the Report Prompt, which prompts for year.

1.     Create your prompt by using the Control object of your choice and assigning the desired data role.
2.     Create a parameter that corresponds to the data type and assign it to the Control object’s Parameter Role.
3.     For the Text object, assign the same parameter to the Text object’s Parameter Role.
4.     Double click on the Text object, use your cursor to add static text as you like.

The steps are similar for the Page Prompt, which prompts for region.

1.     Create your prompt by using the Control object of your choice and assigning the desired data role.
2.     Create a parameter that corresponds to the data type and assign it to the Control object’s Parameter Role.
3.     For the Text object, assign the same parameter to the Text object’s Parameter Role.
4.     Double click on the Text object, use your cursor to add static text as you like.

Even though I demonstrate how to do this for both Report and Page Prompts, this same technique can be used for report canvas prompts. You just have to be sure you store the selected value(s) in a parameter that you can then use in the Text object’s Parameter Role.


Very much the same way the Text object’s Roles are used to assign the Parameter values, we can do the same thing with a measure. This measure will be affected by any Report or Page Prompts automatically, but if you want to use a report canvas prompt you will need to create the Actions to the Text object appropriately.

Here you can see we are using the measure TotalExpense which is an aggregated measure of Expenses. Like in the previous examples, be sure to assign the measure to the Text object then double click to open the editor and use your cursor to add the static text.

The only applied filters for this aggregated measure are the selected year and region, therefore this Sum _ByGroup_ will return the Total Expenses for that Year and Region.

Table Modified Time

The last capability of dynamic text available in the Text object is the Table Modified Time.

The out of the box display uses the fully qualified datetime stamp and cannot be altered to a different format. To edit, double click inside the Text object and the editor will open. Then click on the Table Modified Time button. Next, use your cursor to position where you would like to add static text. In this case, I added the qualifier Data last updated:.


There are two main takeaways from this blog post. First is that you can easily build dynamic customizable titles, emphasize measures or parameter values.

Second, look to use the Text object for your dynamic text needs.

Here is a quick mapping as a review of what was detailed in the steps above.


Using Dynamic Text in a SAS Visual Analytics Report was published on SAS Users.

3月 132018

SAS Visual Analytics 8.2 introduces the Hidden Data Role. This role can accept one or more category or date data items which will be included in the query results but will not be displayed with the object. You can use this Hidden Data Role in:

  • Mapping Data Sources.
  • Color-Mapped Display Rules.
  • External Links.

Note that this Hidden Data Role is not available for all Objects and cannot be used as both a Hidden Data Role and Data tip value, it can only be assigned to one role.

In this example, we will look at how to use the Hidden Data Role for an External Link.

Here are a few applications of this example:

  • You want to show an index of available assets, and you have a URL to point directly to that asset.
  • Your company sells products, you want to show a table summary of product profit but have a URL that points to each Product’s development page.
  • As the travel department, you want to see individual travel reports rolled up to owner, but have a URL that can link out to each individual report.

The applications are endless when applied to our customer needs.

In my blog example, I have NFL data for Super Bowl wins. I have attached two columns of URLs for demonstration purposes:

  • One URL is for each Super Bowl event, so I have 52 URLs, one for each row of data.
  • The second URL is for each winning team. There have been 20 unique Super Bowl winning teams, so I have 20 unique URLs.

Hidden Data Role in SAS Visual Analytics

In previous versions of SAS Visual Analytics, if you wanted to link out to one of these URLs, you would have to include it in the visualization like in the List Table shown above. But now, using SAS Visual Analytics 8.2, you can assign a column containing these URLs to the Hidden Data Role and it will be available as an External URL.

Here is our target report. We want to be able to link to the Winning Team’s website.

In Visual Analytics 8.2, for the List Table, assign the Winning Team URL column to the Hidden Data Role.

Then, for the List Table, create a new URL Link Action. Give the Action a name and leave the URL section blank. This is because my data column contains a fully qualified URL. If you were linking to a destination and only needed to append a name value pair, then you could put in the partial URL and pass the parameter value, but that’s a different example.

That is using the column which has 20 URLs that matches the winning team in the Hidden Data Role. Now, what if we use the column that has the 52 URLs that link out to the individual Super Bowl events?

That’s right, the cardinality of the Hidden Data Role item does impact the object. Even though the Hidden data item is not visible on the Object, remember it is included in the results query; and therefore, the cardinality of the Hidden data item impacts the aggregation of the data.

Notice that some objects will just present an information warning that a duplicate classification of the data has caused a conflict.

In conclusion, the Hidden Data Role is an exciting addition to the SAS Visual Analytics 8.2 release. I know you'll enjoy and benefit from it.

The power behind a Hidden Data Role in SAS Visual Analytics was published on SAS Users.

12月 222017

Another report requirement came my way and I wanted to share how to use our Visual Analytics’ out-of-the-box relative period calculations to solve it.

Essentially, we had a customer who wanted to see a metric for every month, the previous month’s value next to it, and lastly the difference between the two.

Relative Period Report in SAS Visual Analytics

To do this in SAS Visual Analytics, which is available in versions 7.3 and above, use the relative periodic operators. I am going to use the Mega_Corp data which has a date data item called Date by Month using the format: MMMYYYY. SAS Visual Analytics supports relative period calculations for month, quarter and year.
The first two columns, circled in red, are straight from the data. The metric we are interested in for this report is Profit.

Next, we will create the last column, Profit (Difference from Previous Period), which is an aggregated measure that uses the periodic operators.

From the Data pane, select the metric used in the list table, Profit. Then right-click on Profit and navigate the menus: Create / Difference from Previous Period / Using: Date by Month.

A new aggregated measure will be created for you:

If you right-click on the aggregated measure and select Edit Aggregated Measure…, you will see this relative period calculation, where it is taking the current period (notice the 0) minus the value for the previous period (notice the -1).

Okay – that’s it. This out-of-the-box relative period calculation is ready to be added to the list table. Notice the other Period Operators available in the list. These support SAS Visual Analytics’ additional out-of-the-box aggregated measure calculations such as the Difference between Parallel Periods, Year to Date cumulative calculations, etc.

Now we have to create the final column to meet our report requirement: the Previous Period column.

To do this we are going to leverage the out-of-the-box functionality of the relative period calculation. Since this aggregated measure calculates the previous period for the subtraction – let’s use this to our advantage.

Duplicate the out-of-the-box relative period calculation by right-clicking on Profit (Difference from Previous Period) and select Duplicate Data Item.

Then right-click on the new data item, and select Edit Aggregated Measure….

Now delete everything highlighted in yellow below, remember to also delete the minus sign. And give the data item a new name. Click OK. This will create an aggregated measure that will calculate the previous period.

The final result should look like this from either the Visual tab or Text tab:

Now we have all the columns to meet our report requirement:

Now that I’ve piqued your interest, I’m sure you are wondering if you could use this technique to create aggregated data items to represent the Period -1, -2, -3 offset? YES! This is absolutely possible.
Also, I went ahead and plotted the Difference from Previous Period on a line chart. This is an extremely useful visualization to gage if the variance between periods is acceptable. You can easily assign display rules to this visualization to flag any periods that may need further investigation.

Relative Period Report in SAS Visual Analytics was published on SAS Users.