In SAS Intelligent Decisioning (as of stable 2025.10), there has been an update to the sample decisioning workflow.  In a previous blog, I reviewed using the sample workflow for SAS Intelligent Decisioning.  The new version of the sample workflow for SAS Intelligent Decisioning includes a property for controlling the enablement of the Publish button in a decision when using a workflow.  In this post, I will review how you can use that new property in a workflow definition.   The data object for the Publish button property is called idlsPublishing.  If it is set to False then the Publish button is active and if it is set to True then the Publish button is inactive.  By default, for the new sample workflow, this property is set to False, so the Publish button will always be active by default when using the out-of-the-box sample workflow.     Administrator: Set the Publish property   As an Administrator, I followed the steps in a previous post about copying and administering the sample workflow for SAS Intelligent Decisioning.   For the new version of the sample workflow, I first want to change the workflow definition so the Publish button is deactivated when the workflow starts.  To do this, I select the Properties button ( ) for the workflow definition.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   By default, the idlsPublishing property is set to False.     I edit this property and set it to True, so the Publish button will be disabled when the workflow starts.     Next, I want to enable the Publish button after the decision is Approved as part of the workflow process.  To do this, I select the Prepare decision for deployment user task.     I then select its Prompts button ( ) to view the prompts for the selected user task.     I add the following new prompt:     Note:  Since the values for idlsPublshing are only True or False, no attribute values are needed. A checked box is True so button will stay de-activated, an unchecked box is False which re-activates the button.   Next, I select the connection between the Deploy decision user task and the End node.     Then, I select the Path Conditions button ( ).     I add the condition of AND idlsPublishing==”False” to ensure the Publish button is re-activated before the workflow can end.     Finally, I save the workflow definition, create a new version, and activate that version of the workflow definition.     User: Publish feature in action   Now that the workflow definition is all configured by the Administer, authorized users can now use the workflow with decisions.   I log on as a user who is authorized to use the workflow and add the workflow to a decision.  The workflow is not started and the Publish button is active.     I start the workflow and the Publish button is now inactive.     I work my way through the workflow process and once the decision is Approved at the Prepare decision for deployment step when I complete that task, I have the ability to activate the Publish button.     By unchecking the box, the Publish button is now activated and the user can Publish the approved decision.     Once the decision is published, I claim and complete the Deploy decision task and the workflow is complete.       Summary   The workflows for SAS Intelligent Decisioning now include a new property (idlsPublishing) that you can use to enable or disable the Publish button for a decision when using a workflow.  For more information, refer to the Controlling Publishing from within a Workflow section in the documentation.     Find more articles from SAS Global Enablement and Learning here. ... View more

In SAS Studio, Snippets are located on the left-hand navigation pane.  Code snippets are useful for providing example code for performing various tasks.  As of the stable 2025.09 release, snippets are now added as embedded program steps to your SAS Studio Flow.  Embedded programs are stored within the flow itself. You can access and edit an embedded program only from within the flow.   I will start with this SAS Studio Flow to walk through an example of adding snippets to a SAS Studio Flow.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   I want to add steps to this flow, so that the output table CARS_INFO is written to an in-memory CAS table.   The first thing I need to do is to find the snippet I want to use to create a CAS session and create SAS librefs for my caslibs.  The Snippet that meets that criteria is Generate SAS librefs for caslibs listed under Viya Foundation → Cloud Analytic Services on the Snippets navigation pane of SAS Studio.     Note: I right-clicked on the snippet and selected the option Open as text to view its code.   Now, that I have selected the snippet I want, I right-click and select the option Add to flow.  This adds the snippet as an embedded program node to the flow file.     Since I want this code to run before my existing flow in the Cars Info swimlane, I adjust the swimlane order and give it a name.  I also save the changes to my flow file.     Next, I add the Delete Table or File from caslib snippet to the flow and rename the new swimlane.  I am doing this to prevent any issues if I re-run this flow in the future and the table already exists in my CAS library.     I click on the Delete Table or File from caslib code step in the flow to view its code.     I change the placeholders for “tableName” and “sourceCaslib” to the values needed for my flow and save it.     Next, I drag the Load Data to caslib snippet to my Write Table to CAS and Terminate Session swimlane.     I click on the Load Data to caslib code step in the flow to view its code.   It has three examples for loading data to a caslib.  For the purposes of my flow, I want to use the second code block.     Therefore, I delete the other two code blocks.     Then, I change the placeholders for “library”, “tableName”, “myCaslib”, and “targetTableName” to the values needed for my flow.  I add the command promote to promote the table to in-memory in CAS and save it.     Finally, I drag the Terminate CAS Session snippet to the Write Table to CAS and Terminate Session swimlane on my flow and view its code. No code changes are needed for my flow.     I save and run the flow.     I navigate to SAS Data Explorer to view the resulting CARS_INFO table loaded into memory in my DM CAS library.       Summary   Using code snippets is helpful to use as a reusable template for any custom code needed for your SAS Studio Flows.  As of the stable 2025.09 release, code Snippets from the left-hand navigation pane of SAS Studio are now added as embedded program steps to your SAS Studio Flow.  For more information, refer to the documentation.     Find more articles from SAS Global Enablement and Learning here. ... View more

In SAS Intelligent Decisioning, a value list is a list of acceptable values for a variable.  A value list can either be a character list or a numeric list.  A value list is required for a variable that is used to create a branch or a matrix in a segmentation tree.     As of stable 2025.06 there are now two types of value lists:   Value lists that are defined on the Value Lists page and Local value lists that are defined on the Segmentation Trees page.     Value lists defined on the Value Lists page can be used in any segmentation tree.  Local value lists are defined as part of a segmentation tree and can only be used in that segmentation tree.     Defining a Value List on the Value Lists Page   On the Value Lists page ( ), select New value list. Enter a name for the value list, select its type, enter a description, and select the location in which to save it.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   Select   to add a value to the list.     Enter the value and its label.  Repeat this process until all the list values have been entered.     Note:  use “v” to represent value in a numeric range of values.  For more information, refer to the help topic Specifying Value List Entries.     By default, an entered value is enabled; however, you can toggle the Enabled option to off if needed.     This value list can be assigned to a variable on any segmentation tree.     Defining a Local Value List   A local value list is defined as part of a segmentation tree; therefore, it is defined on the Segmentation Trees page ( ).  Open a segmentation tree and then from the Segment Tree tab, click a   to open the Local Value Lists sub-tab.      Select   to create a new local value list.  The first step is to define the local value list by entering a name and selecting whether you want to copy a value list or create a unique local value list.  If you create a unique local value list, then select its type.     Select Next to move on to the second step of adding values. Select   to add a value to the list.  Enter the value and its label.  Repeat this process until all the list values have been entered.     Select Finish to complete the definition of the local value list.  This local value list can only be assigned to a variable on this segmentation tree.   As of stable 2025.07, you can delete a local value list by selecting   and then clicking Delete.       Summary   In SAS Intelligent Decisioning, there are now two types of value lists that can be used in segmentation trees. For more information, review the documentation on Using Value Lists and Using Local Value Lists.     Find more articles from SAS Global Enablement and Learning here. ... View more

In SAS Intelligent Decisioning, if an object is saved in a folder where the administrator has enabled the check-out and commit feature, then the object must be checked out by a user to make any edits to it.  If this feature has been enabled for a folder, then the Check out button is displayed on the Versions tab for the object.  Once an object is checked out, then a Commit button is displayed on the Versions tab for the object.   By default, the Check Out and Commit feature is enabled for the Decision Repository folder in SAS Content.  Users cannot edit objects saved in the Decision Repository folder without first checking them out.   Let’s walk through a demo of the Check Out and Commit feature.  Notice that the Loan_Request_Review decision is saved in a sub-folder of the Decision Repository folder.  Therefore, to edit this decision, I must first check it out.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.     When I open the Loan_Request_Review decision it is opened as Read-only.     On the Versions tab, there is a Check Out button.     Click the Check Out button, to check out the decision and its related objects for editing.     This creates a working copy of the decision in the My Folder location of the user that is logged in.  The working copy of the decision has a check mark in the Checked Out column in the listing of the objects and the original decision with the same name is also listed.     I can make any desired changes to the checked out decision or can open one of its related objects and check it out to make changes to it.  For example, maybe I want to change the code in my Reduce_Offer_Rate node.  I open that node and select its Check Out button on the Versions tab.     The Reduce_Offer_Rate code file is checked out.     The checked out copy is in the My Folder location of the user that is logged in.  The working copy of the code file has a check mark in the Checked Out column in the listing of the objects and the original code file with the same name is also listed.   I make the desired changes to the code file and save it.  This simply saves the changes to the working copy in the My Folder location. On the Versions tab, there is a Commit button displayed there.     Select the Commit button to make the changes to the main file and create a new version.  Select whether you are creating a Minor or Major version, add any tags and notes as needed and select Commit.     This creates a new version of the main file and deletes the working copy in the My Folder location.     Back in the working copy of my Loan_Request_Review decision, I change the Reduce_Offer_Rate node to use the new version I just created and save it.  This saves the changes to the working copy of the decision in the My Folder location.     On the Versions tab, I select the Commit button to commit the changes to the main decision file and delete its working copy.       Summary   In SAS Intelligent Decisioning, if you save your objects in a specified folder where the check out and commit feature has been enabled, then you must check out that object to edit it and commit it before others can view the changes. For more information, review the documentation on the Check Out and Commit feature.     Find more articles from SAS Global Enablement and Learning here. ... View more

In SAS Intelligent Decisioning (as of stable 2025.03), you can manage workflow tasks on the Home page. The Tasks section at the bottom of the home page lists the active workflow tasks to which you or a group of which you are a member have been assigned. You can claim, complete, and release tasks from the Home page.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   In my previous post, I reviewed the administrative tasks for setting up workflow for SAS Intelligent Decisioning.  In this post, I will demonstrate using that workflow with a decision as a non-Administrator.     Add a Workflow to a Decision   There are two ways to add a workflow to a decision.  One way is to select the workflow when you create the decision.       The other way is to add it on the properties tab after the decision is created.       I have added the Decision Approval workflow that I created in my previous post to the decision.     Workflow Tasks   As a reminder, the Decision Approval workflow consists of the following user tasks:   Develop decision Review decision Prepare decision for deployment Deploy decision.     All workflow users can perform the Develop decision and Review decision tasks; however, Alex is excluded from being a participant in the Prepare decision for deployment task and Alex and Sarah are excluded from being participants in the Deploy decision task.     Currently, there is no tie between tasks and permissions to perform functions such as publishing a decision; therefore, even though in the workflow Alex and Sarah are excluded from the Deploy decision task they can still publish the decision.     Start a Workflow There are two ways to start a workflow for a decision.  One way is to select the Workflow dropdown button and then select Start workflow.     The other way is to select Start on the Properties tab of the decision.       Using either method opens a dialog box.  If the workflow requires inputs to start, then you will be prompted to complete them; otherwise, simply select Start.       The workflow now shows the status of the first step in the workflow.  In the case of the Decision Approval workflow that is Developing.       Claim Task I am logged in as the user Alex and select Tasks →  Develop Decision from with the decision.     Next, I select Claim to claim the task and then Close to close the dialog.     Alex has claimed the Develop decision task.  The task is removed from the general queue for claiming and is assigned to Alex.  Tasks can also be claimed from the Tasks list on the Home screen if they are still unclaimed.       Since Alex has claimed the Develop decision task.  When I log in as Sarah, there are no tasks for her to claim since Alex is already working on it.       Complete Task Alex works on developing the task and when he is ready, he can set the Develop decision task to complete by selecting Tasks →  Develop Decision  and then click Complete.       He moves the decision to the Review Ready stage and can enter any desired comments.       Depending upon workflow there may be more than one next task to select when completing a task.  Now that this task is complete the next task in the workflow is ready to be claimed.     Tasks can also be completed from the Tasks list on the Home screen if it is still incomplete and has been claimed by the user who is logged in.       Release Task If a user has claimed a task and decides they will not work on that task, they can release the task so another user can claim it and work on it.  To do this, on the task dialog select Release and then Close.       Releasing a task unassigns the task and puts it back in the general queue for another user to claim.  The task stays at the same status.     Tasks can also be released for the Tasks list on the Home screen if they have been claimed by the user who is logged in.     Complete Workflow Once all tasks for a workflow have been completed, the workflow is marked Completed in the decision.       If you create a new version of the decision, then you can start the workflow process again.                        Summary   You can use a workflow to formalize the decision building, approval, and publishing process.  You can work with the workflow tasks from either within the decision or from the Home screen.  For more information, refer to the Using Custom Workflows with SAS Intelligent Decisioning section in the documentation.     Find more articles from SAS Global Enablement and Learning here. ... View more

In SAS Intelligent Decisioning (as of stable 2025.03), you can manage workflow tasks on the Home page. The Tasks section at the bottom of the home page lists the active workflow tasks to which you or a group of which you are a member have been assigned. You can claim, complete, and release tasks from the home page.   Before any tasks will be listed on the home page, an Administrator must first configure the workflow(s) for use with SAS Intelligent Decisioning.  In this post, I will review these workflow configuration activities by using the Sample Decision Approval workflow as an example.   Workflow Administration   Workflows are administered in the SAS Workflow Manager application.  This application is accessed from the Viya menu by selecting the Manage Workflows option under the Administration area.  There are some sample workflow definitions that are delivered as part of the SAS Viya installation.  The Client Identifier column indicates the application where the workflow can be used.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   For this demo, we will focus on the Sample Decision Approval workflow for SAS Intelligent Decisioning.     Selecting the hyperlink on the workflow definition name opens the workflow.  Below is the workflow definition for Sample Decision Approval.     The Sample Decision Approval workflow has four user tasks:   Develop decision Review decision Prepare decision for deployment Deploy decision.   It is recommended to create a copy of any of the sample workflow definitions before making any changes. To copy the Sample Decision Approval workflow definition, I select the More options menu and then Save as.     I name my copy of the workflow definition Decision Approval.     I select the Definition properties button to view its settings.     I select the Client identifier of SAS Intelligent Decisioning to enable this workflow definition for use in that application.     I then select  to create version 1.0 of this workflow definition and it is automatically activated since there is only one version.  I can confirm this on the Versions tab.       Authorize a Workflow   Before any users can select a workflow and start it, they must be granted Read permission to the workflow definition.  To do this, an administrator must first open the workflow definition.  Select the More options menu and then Authorization.     Select the user(s) and/or group(s) that should have permission to use the selected workflow definition and set the authorization to Read.  An administrator may want to create group(s) for this purpose.  In my case, I created a group called Workflow Users and added several user(s) to that group.       Add Participants to Workflow Tasks   On each user task within the workflow definition, an administrator needs to add the user(s) and/or group(s) who should have permission to participate in that task.   For the Develop decision user task, I add the Workflow Users group as a Participant.     For the Review decision user task, I add the Workflow Users group as a Participant.     For the Prepare decision for deployment user task, I add the Workflow Users group as a Participant.  I also exclude the user Alex as a participant.     For the Deploy decision user task, I add the Workflow Users group as a Participant. I also exclude the users Alex and Sarah as a participant.     I save the workflow definition and select  to create a new version of the workflow.  I then select  to activate this version.  I confirm the activation of the workflow definition version on the Versions tab.       Configuration Settings   It is recommended that an administrator turn on the sas.businessrules.publish.hideRuleSetPublish configuration property.  If turned on, then the Publish button is hidden for rule sets. It is recommended that you turn on this property so that all published content is developed in a decision's workflow.  For more information, refer to its documentation.     Optionally, an administrator can also configure the length of time that workflow history items are retained using the sas.workflowhistory.eventlog configuration property. The default is 30 days. For more information, see Configure History Event Properties in SAS Workflow Manager: Administrator’s Guide.       Summary   Workflow tasks are now integrated on the Home screen of SAS Intelligent Decisioning.  However, before you can use workflows with decisions, an administrator needs to perform some configuration.  In this post, I acted as an administrator and configured the Decision Approval workflow.  In my next post, I will demonstrate how to use this Decision Approval workflow in a decision.   For more information, refer to the Configure SAS Workflow for Use with SAS Intelligent Decisioning documentation.     Find more articles from SAS Global Enablement and Learning here. ... View more

In SAS Intelligent Decisioning (as of stable 2024.11), you can now view segmentation trees as a graphical diagram.  In a previous post, I introduced the concept of using segmentation trees in a decision.  In this post, I am going to show some enhancements that have been made to segmentation trees that enable you to visualize them graphically.   As a reminder, below is what the example segmentation tree I built in that previous post looks like in releases prior to the stable 2024.11 release.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   And this is what the example segmentation tree looks like as of the stable 2024.11 release.     As of the stable 2024.11 release, you now have two views you can select from on the Segmentation Tree tab – Table view and Graph view.     You can build and edit the segmentation tree from either view.  This gives you the flexibility to work in the view you prefer.   The tree elements panel has also changed as of stable 2024.11 release.  The sections Boolean expressions, Matrices, and Variables have been divided into separate tabs on the left-hand side.     Table View   Here is what the table view of the example segmentation tree I built in the previous post looks like as of the stable 2024.11 release.     It is the same as it was in previous releases.   Graph View   New as of the stable 2024.11 release is the graph view of a segmentation tree.  Here is what the graph view of the example segmentation tree I built in the previous post looks like as of the stable 2024.11 release.     This gives a nice visual depiction of the segmentation tree and another way for you to work with it if you prefer.   On the graph view you can Zoom in, Zoom out, Zoom to fit, view an Overview Window, and highlight a Path.     Summary   As of the stable 2024.11 release, you now have the option to work with Segmentation trees in a visual mode.  This gives you the flexibility to work with the segmentation tree in a tabular and/or graphical form. For more information, refer to the SAS Intelligent Decisioning documentation on Working with Segmentation Trees.     Find more articles from SAS Global Enablement and Learning here. ... View more

In SAS Intelligent Decisioning (as of stable 2024.01 or LTS 2024.03), you can create advanced lists and reference them in rule sets.  Advanced lists can also be shared among SAS applications and workflows.   An advanced list is a tabular data set that can have multiple keys and values.  It enables you to manage tabular data in your environment allowing you to publish and query that data in a low-latency, key-value data store.  Advanced lists also provide the ability to protect sensitive data in your lists using data masks. When you mask data in a list, all or a portion of the data values for an entire list column are redacted in the output.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   Advanced lists are stored in Redis. You must provide, configure, and maintain your own Redis instance. For information about configuring Redis for your environment, refer to the List Data Service topic in the SAS Viya: Administration guide.  In addition, an administrator must add any users who need to work with advanced lists to the Advanced List Users custom group in SAS Environment Manager.     Creating an Advanced List   To create an advanced list, select New list on the Advanced Lists page within SAS Intelligent Decisioning.​     The first step in creating in advanced list is to define its properties.  You must enter a name for the advanced list.  Optionally, you can also specify a label and description.     Check the box for deploy list on creation if you want the advanced list to be available for use by other SAS applications and workflows upon its creation.  If you don’t check this box now, you can deploy the list after creation.  Check the box for is immutable to prevent the contents of the list being changed after you add data.     The Products\List Data folder in SAS Content is the default location for storing new advanced lists.  If you want to store it in a different location, select the folder icon and navigate to that location.     For the list content, you have the option to define an empty list or import its contents from a CSV file.  You also have the option to include an expiry date column for the list items.     Next, review the column names from the imported CSV or if creating the list from scratch, then add the column names for your advanced list. If you are importing the items from a CSV file, the column names are taken from the first row of the file.  Confirm you have selected the correct data type for each column.  The available data types are string, numeric, datetime, currency, and currency code.   You can also select whether you want to mask the column.  When masking a column, you can mask all characters or all but the last four characters.  Currently, if you mask the data in a column, then that column cannot be returned in a rule set.  Also, do not select to mask any of your key columns.     Finally, select one or more columns to be the key for your advanced list.  In other words, what column or columns are used to uniquely identify a row on your advanced list.  Select Finish to create your advanced list.     Here is the created advanced list with the data imported from the specified CSV file.     In this case, CLIENT_ID is the key column and EMAIL, PHONE1, and PHONE2 are the value columns.  Depending on your privileges, you may be able to view and/or edit the list properties and its items.   The status of a list item can be deployed, developing, or archived.  Archived is only a status option if you have set an Expiry column for your advanced list. I select to deploy all rows for my advanced list.     This changes all the list items to the status of deployed.  Only deployed items are returned when referencing an advanced list.       Referencing and Advanced List in a Rule Set   Once a list is deployed, you can use an advanced list reference in an assignment or common rule set to retrieve values from the list.     The first step is to select the advanced list you want to reference.  Only deployed advanced lists are available for selection here.     Next, select the value columns you want to retrieve.  Only the value columns that are not masked are listed here.     Finally, map the input variable or variables to the key column or columns on the advanced list.  Select Finish to complete the reference logic for the rule set.     This is what the reference to the advanced list looks like in the rule set.     Below are the results of testing that advanced list reference.       Summary   The advanced lists features enable you to manage tabular data in your environment and query that data in a low-latency, key-value data store. For more information, refer to the SAS Intelligent Decisioning documentation on Managing Advanced Lists.     Find more articles from SAS Global Enablement and Learning here. ... View more

In SAS Intelligent Decisioning (as of stable 2023.12 or LTS 2024.03), you can add a Parallel Process node to a decision.  This node processes multiple decisions in parallel within a decision.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   There are several rules that must be followed when using a Parallel Process node in a decision.​   A parallel process node can contain only decisions. The same decision cannot be added to the same parallel process node more than once.​ None of the decisions or their sub-decisions that are added to a parallel process node can contain parallel process nodes.​ All the decisions that are added to a parallel process node must return exactly one output variable of type data grid. For all decisions that are included in the same parallel process node, input variables that have the same name must have the same data type, and the columns in the output data grids that have the same name must have the same data type.   You can publish decisions that contain parallel process nodes to SAS Micro Analytic Service (MAS), Container destinations, and SAS Cloud Analytic Services (CAS). By default, decisions in a parallel process node are processed in parallel only for MAS and Container destinations. In CAS, the decisions in the parallel process node are processed sequentially.​   ​To successfully execute the decisions in parallel process nodes, you must configure the time-out limit and the maximum number of threads for the destination to which you publish decisions that contain the parallel process nodes. For more information, refer to the Configuring Support for Parallel Process Nodes topic in SAS Intelligent Decisioning: Administrator’s Guide.​     Example Decision with Parallel Process Node   Here is an example decision using the Parallel Process node.     The parallel process node executes two sub-decisions at the same time.  These two sub-decisions use two slightly different methods to determine if a customer’s mortgage is underwater (i.e., the customer owes more than the property is worth).  Note:  I could add other nodes before or after the parallel process node in the decision flow, but for the purposes of this post solely focusing on the parallel process node.   Let’s look at both of the sub-decisions from the Parallel Process node.     Both of the sub-decisions only have one Output variable, and it is of type data grid.  Also, they both have an Input variable called CLIENTID and in both sub-decisions it has the same data type of Character.     For both sub-decisions where their Output data grids have the same variable names they are also of the same type.     The main decision has the needed Input and Output variables.     The PPN_OUT_1 data grid is the merged data grid of all the sub-decisions in the Parallel Process node.  It also includes columns related to the Parallel Process node (PPN_ columns).  For example, the PPN_DECISION_NAME column lists which sub-decision produced the row in the data grid.     Now, let’s test the Parallel Process decision.  Here you can view in the output data grid which sub-decision produced the row in the output.       Summary   Using a Parallel Process node in a decision is especially useful when you have many sub-decisions that require a significant amount of input and output operations or that have a lot of complex logic, and all these decisions need to be run before a final decision is reached. For more information, refer to the SAS Intelligent Decisioning documentation on Adding Parallel Processing Nodes.   You can also build the example decision using the Parallel Process node from this post by taking the SAS Intelligent Decisioning: Beyond the Essentials course.     Find more articles from SAS Global Enablement and Learning here. ... View more

In SAS Intelligent Decisioning (as of LTS 2023.10), you can create segmentation trees and value lists.   A segmentation tree is a hierarchical structure that consists of a root node, branches, and final leaf nodes called outcomes. Any branch can lead to additional branches or to an outcome. Each branch in the tree specifies criteria that determine whether that particular branch is executed. The criteria for a branch might be Boolean expressions, individual variable values, or combinations of variable values called a matrix.  Outcomes define actions to be taken when all of the branch criteria leading to the outcome are satisfied.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   When defining a variable for the segmentation tree, you can associate the values of the variable to a value list. A value list is the list of acceptable values for a variable.  Value lists are used for Segmentation tree branches of type Variable or Matrix.   For a large, complicated decision that uses simple conditions, a segmentation tree can be an effective way to visually represent the decision's model and to manage the associated outcomes.   Value Lists   Value lists can be of type Character or Numeric.     The entries in a numeric value list can be discrete values or ranges.   To specify a range of numeric values, use v to indicate the value of the variable that is associated with the list. Numeric ranges cannot overlap.  To enter multiple value specifications in one entry, separate the specifications with a semicolon.  Multiple entries within the same list cannot specify the same value.   Here is an example of a value list for credit score ranges.     For more information, refer to the Specifying Value List Entries topic in the SAS Intelligent Decisioning documentation.   Segmentation Trees   SAS Intelligent Decisioning provides a low-code interface for designing segmentation trees, and it displays the segmentation tree in a simplified, compact format.  The three main elements used to build a segmentation tree in SAS Intelligent Decisioning are: Variables, Branches, and Outcomes.   Just like other objects in SAS Intelligent Decisioning, you list the variables needed for segmentation trees on the Variables tab.  For each variable, you specify a name, data type, whether it is an input, an output, both, or neither.  You can also specify an Initial value for an output variable.   What is different about variables for a segmentation tree is that you can associate a value list with a variable; this means that values for this variable come from the associated value list.     There are three types of elements used to create branches in a segmentation tree – Boolean expression, Matrix, and Variable. When you add one of these elements to a segmentation tree, SAS Intelligent Decisioning creates branches for each of the possible values or result strings that can be produced by the element. For each value or result string, you can either add an outcome to be executed, or you can add additional branch elements to the tree.   A value list must be associated with the variable that is used to create the branch type of variable or matrix. A matrix requires two variables associated with different value lists thus producing a matrix whereas a variable branch is a single variable associated with a value list.     An outcome is the last leaf in a segmentation tree branch. An outcome is a named set of actions to be taken when all the branch conditions leading to the outcome are satisfied. An outcome can be one or more assignment statements, one or more DS2 code files, or a combination of both. You can reuse the same outcome in multiple places in a tree. You can also customize each instance of the same outcome as needed.       Using a Segmentation Tree in a Decision   I can now finally use the segmentation tree in a decision flow.  Adding a segmentation tree to a decision flow is similar to adding any other object to the flow.  Once the segmentation tree is added, you can select to open it in its editor.  You can publish a decision with a segmentation tree to any of the publishing destinations.       Summary   Using Segmentation Trees with value lists in your decisions can be a useful combination for representing your decision logic.  For more information, refer to the SAS Intelligent Decisioning documentation on Using Value Lists and Working with Segmentation Trees.     Find more articles from SAS Global Enablement and Learning here. ... View more

In SAS Intelligent Decisioning when creating rule sets, you can create a Common rule set that can be referenced by many Assignment rule sets.  When an Assignment rule set containing a reference to a Common rule set executes, the Common rule set is executed as if it was defined directly in the Assignment rule set.   Let’s look at an example of creating and referencing a Common rule set in SAS Intelligent Decisioning.   When creating the Common rule set, you must select the type of Common.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   Building a Common rule set is the same as building an Assignment rule set.  You can use IF-THEN-ELSE logic and add assignments.  Here is the Common rule set, I have built for this example.     Next, you need to create a rule set of type Assignment.  Common rule sets can only be referenced in Assignment rule sets; they cannot be referenced in a Filtering rule set.     In this rule set, select Add rule and then select Common rule set reference to open the Add Common Rule Set References dialog.     Note: If rules have already been added to this assignment rule set, then you select Add > Add reference.   First step, select the Common rule sets, you want to add as a reference, then select Next.     Second step, select the version to reference for each of the selected Common rule sets, then select Next.     Note: If this referenced version of the Common rule set changes, then the new logic is used by this Assignment rule set.   Third step, map the input variables.  You can select Add Missing Variables to automatically add the input variables from the Common rule set to the Assignment one you are creating.     Fourth step, map the output variables.  You can select Add Missing Variables to automatically add the output variables from the Common rule set to the Assignment one you are creating.     Fifth step, order the selected Common rule set references using the arrow buttons and select Finish.     The Common rule set(s) are referenced in the Assignment rule set.  You can add other rules within this Assignment rule set and test and publish this Assignment rule set that contains a reference to the Common rule set as needed.     You can also expand any referenced Common rule set to view its current logic.     Summary   The use of Common rule sets allows for reusability of rule logic and if a change is needed, then you only need to make it in one place.  For more information, refer to the SAS Intelligent Decisioning documentation on Rule Set Types.     Find more articles from SAS Global Enablement and Learning here. ... View more

As of the stable 2024.04 SAS Viya release, you can specify whether the values for the column selector control in a custom step come from an input table or from another column selector control.   Here is the new option:   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   In this example custom step, the first column selector has its selections tied to an input table.     The second column selector is tied to the first column selector which means its available values for selection will come from the values selected in the first column selector.     Note:  The Link to column selector option lists the column selector controls in the step that are linked to input tables. This list does not include column selectors that are linked to another column selector control. In other words, the second column selector will not show as possible link to another column selector.   I also used a new style feature available for custom step controls to indent the second column selector to make it more visually obvious that is related to the first column selector.     When I preview the custom step, I can select certain columns for the first column selector control.     Once I have selected those four columns for the first column selector control, I can only select from those for the second column selector control.     Summary   This is an enhancement to the column selector control that you can take advantage of in your custom step design.  For more information on the Column Selector control in a custom step, refer to the following: Column Selector Control documentation SAS Studio Custom Steps - Coding Made Easier Using the Column Selector Control blog SAS Viya: Using Cascading Prompts in a Custom Step blog. ... View more

As of the Viya stable 2024.01 release, there is a Link control for Custom Steps. Use the Link control to add hyperlinks to the user interface of your custom step design. For security reasons, this feature must be enabled by a SAS administrator in SAS Environment Manager on the Configuration page before it can be added to a custom step.   Enable Link Control for Custom Step   A SAS administrator must log on to SAS Environment Manager to configure the use of the Link control in a Custom Step.  On the Configuration Page, search for flow.  Select the Data Flow service.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   For sas.data.flows section, select  to edit the settings for the allowedStepLinks option.     Add supported domains (e.g. https://, file://, vscode://, etc.) in the format of a regular expression (regex) and use the OR character (|) in a regular expression to separate multiple domains.  Note: JavaScript is not supported.  I enter the following regular expression and select Save.   ^https?:\/\/(?:.+\.)?sas\.com(?::\d+)?(?:\/.*)?|^vscode:\/\/file\/C:\\.+     This allows links to be added in Custom Steps for https:// for various sas.com sites OR files to open in VSCode that are only located on the C:\ drive.   For help with regular expressions, you can visit the site https://regexlearn.com/.   Use Link Control in a Custom Step   In the Custom Step Designer, there is now a Link control.     I add the Link control to my custom step canvas and enter the link: https://learn.sas.com.     I select Preview and the link is displayed since it matches one of the regex patterns entered in the configuration.     I select the link and website for the entered link is opened in the browser.     I now change the link to: https://google.com.     I select Preview and a message is displayed that link does not match one of the regex patterns entered in the configuration.     I now change the link to: vscode://file/C:\PSGEL315-sas-viya-sas-studio-flow-and-custom-steps\README.md     I select Preview and the link is displayed since it matches one of the regex patterns entered in the configuration.     I select the link and specified file is opened in VSCode.     Note:  You may have issues with using the link control especially the file:// protocol.  Exposing local system files is a major security concern that browsers handle in their own ways.  You may need to adjust some settings and/or add browser extensions.  Some variables that are out of SAS Studio’s control are:   The browser being used. The version of the browser being used; policies change with every release. The company IT policies (whether company guidelines or via managed software).   Summary   There is now a Link control in Custom Steps that you can use to add hyperlinks to your custom step user interface.  This allows you to link to sites and files that provide more information to aid the user in completing the user interface of your custom step or provide some documentation/background about the custom step.  For more information, refer to the documentation.     Find more articles from SAS Global Enablement and Learning here. ... View more

As of the Viya stable 2023.11 release, you have the option to change the default library for the writing of temporary output tables when executing a flow in SAS Studio.  This new option only applies to SAS Studio Flows.   By default, the WORK library is used but you now have the option to set a different library for these temporary tables.  You can set this option for all SAS Studio flows you create or set it for a single SAS Studio flow.   Set for All SAS Studio Flows   In SAS Studio, select Options → Preferences from the menu.  Select Tables to view the table preference options.  The newly added section is Default Output Libraries.   Select any image to see a larger version. Mobile users: To view the images, select the "Full" version at the bottom of the page.   The application default is the WORK SAS library.  Select the radio button for Output library location and then select   and navigate to the library you want to set as the new default for SAS Studio Flows.     Click Save to save the default output library selection.  This sets the default output library for all your SAS Studio Flows.   Set for Single SAS Studio Flow   Open the SAS Studio Flow where you want to set a different default output table library option.  On the right-hand side of the flow, select    to open the Properties pane for the flow.     In the Default output library for intermediate tables section, the application default is the WORK SAS library.  Select the radio button for Output library location and then select    and navigate to the library you want to set as the new default for SAS Studio Flows.     Save the flow to save the change to the properties.  This sets the default output library just for this SAS Studio Flow.   Summary You can now change the location where temporary output tables are written when executing a SAS Studio Flow.  For more information, refer to the documentation.   Find more articles from SAS Global Enablement and Learning here. ... View more