SAS Professional Services

9月 082017

In SAS Visual Analytics 8.1, report creators have the ability to include drive-distance and drive-time in their geographical maps, but only if their site has an Esri ArcGIS Online account and they have valid credentials for the account.

In the user Settings for SAS Visual Analytics Geographic Mapping 8.1 release, there are three choices for selection of a geographic map provider.  The map provider creates the background map for geo maps and for network diagrams that display a map.

The map provider options are:

  • OpenStreet Map service, hosted at SAS.
  • Esri ArGIS Online Services, which only requirFinale acceptance of the terms and conditions.
  • Esri premium services, which requires a credential validation.

If Esri premium services is selected, there is an additional prompt for valid credentials, and you must still accept the Esri ArcGIS Online Services terms in order to select the premium services checkbox.

It’s also worth pointing out here, that even if you have Esri premium credentials, in order for these credentials to be validated in SAS Visual Analytics, you must also be a member of the ESRI Users custom group.  Users can be added to this group in SAS Environment Manager, as shown below.

Note that without the Esri ‘premium’ service and validated credentials, when you right-click and Create geographic selection in your report map, you are only able to select the Distance selection, which displays the radial distance for the selection point.

With premium services in effect, you can also select drive-time or drive-distance.  An example of a drive-time selection is shown here.  Drive-time creates an irregular selection based on the distance that can be driven in the specified amount of time.

A drive-distance example is shown below.  Drive-distance creates an irregular selection based on the driving distance using roads.

When selecting drive-time or drive distance, you can also add breaks to show, as in the example below, the 5-mile distance, the 10-mile distance, and the 15-mile distance on the maps.

It’s also worth pointing out, that if a viewer of the report has not had Esri premium credentials validated, the viewer will be unable to view the drive-distances and drive-time features.  The settings for users of the report viewer are also stored in the Report Viewer Geographic Mapping user settings.

If a user is adding a connection to the server in SAS Mobile BI 8.15 and their account is a member of the Esri Users group, they will be prompted for their Esri premium credentials when adding the server connection:

I hope you’ve found this post helpful.

How do I access the Premium Esri Map Service for my SAS Visual Analytics reports? was published on SAS Users.

8月 182017

SAS Viya deployments use credentials for accessing databases and other third-party products that require authentication. In this blog post, I will look at how this sharing of credentials is implemented in SAS Environment Manager.

In SAS Viya, domains are used to store the:

  • Credentials required to access external data sources.
  • Identities that are allowed to use those credentials.

There are three types of domains:

  • Authentication stores credentials that are used to access an external source that can then be associated with a caslib.
  • Connection used when the external database has been set up to require a User ID but no password.
  • Encryption stores an encryption key required to read data at rest in a path assigned to a caslib.

In this blog post we will focus on authentication domains which are typically used to provide access to data in a database management system. It is a pretty simple concept; an authentication domain makes a set of credentials available to a set of users. This allows SAS Viya to seamlessly access a resource. The diagram below shows a logical view of a domain. In this example, the domain PGAuth stores the credentials for a Postgres database, and makes those credentials available to two groups (and their members) and three users.

How does this work when a user accesses data in a database caslib? The following steps are performed:

1.     Log on to SAS Viya using personal credentials: the user’s identity is established including group memberships.

2.     Access a CASLIB for a database: using the user’s identity and the authentication domain of the CASLIB, Viya will look up the credentials associated with that identity in the domain.

3.     Two results are possible. A credential match is:

  • 1.     Found: the credentials are passed to the database authentication provider to determine access to the data.
  • 2.     Not found: no access to the data is provided.

To manage domains in SAS Environment Manager you must be an administrator. In SAS Environment Manager select Security > Domains. There are two views available:  Domains and Credentials. The Domains view lists all defined domains. You can access the credentials for a domain by right-clicking on the domain and selecting Credentials.

The Credentials view lists all credentials defined and the domains for which they are associated.

Whatever way you get to a credential, you can edit it by right-clicking and selecting Edit. In the edit dialog, you can specify the Identities (users and groups) that can use the credential, and the User ID and Password of the credential.  Note that only users who are already listed in the Identities field will be able to edit this field, so make sure you are in this field (directly or through group membership) prior to saving.

To use an authentication domain, you reference it in the CASLIB definition. When defining a non-path based CASLIB you must select a domain to provide user credentials to connect to the database server. This can be done when creating a new CASLIB in SAS Environment Manager in the Data > Libraries area.

If you use code to create or access your caslib, use the authenticationdomain option. In this example, we specify authenticationdomain in the table.addcaslib action.

If a user is not attached to the authentication domain directly, or through a group membership, they will not be able to access the credentials. An error will occur when they attempt to access the data.

This has been a brief look at storing and using credentials to access databases from SAS Viya. You can find  more detail in the SAS Viya Administration Guide in the section titled SAS Viya sharing credentials for database access was published on SAS Users.

8月 172017

In this blog post I am going to cover the example of importing data into SAS Viya using Cloud Analytic Services (CAS) actions via REST API. For example, you may want to import data into a CASLib via REST API.  This means you can perform an import of data outside of the SAS Self-Service Import user interface environment using REST API.  Once this data is loaded into CAS it is available for use in applications such as SAS Visual Analytics and SAS Visual Data Builder.


To import data into SAS Viya via REST API, you need to make a series of REST API calls:

1.     Start CAS Session
2.     Load Data into a CASLib
3.     End CAS Session

I will walk through these various REST API calls in the sections below using the REST API testing application HTTPRequestor, which is a free add-on to the Mozilla Firefox browser.

Before I perform any of my REST API calls, I need to Base-64 encode my credentials. The input for encoding the credentials is: I used the site to encode my credentials.  Note: You can use other methods (e.g., Python) to encode your credentials. Use the preferred method by your organization to ensure you are meeting their security protocols.

Below is the header Authorization information I will be sending with each of my requests.

Authorization Header

1.     Start CAS Session

First, I need to start a CAS Session. Below is an example request for starting a CAS Session:

POST https://<YourCASServer:Port>/cas/sessions

Authorization: Basic <Base-64EncodedCredentials>
 Content-Type: application/json


This request returns the CASSessionUUID needed in the next step.

I construct my request in HTTPRequestor as follows and submit the request:

Start CAS Session Request/Response

Here is a screenshot of the raw transaction information.

Start CAS Session Raw Transaction

I need to copy the CAS Session UUID information that was returned for use in the subsequent REST API calls since their CAS Actions must be performed within a CAS Session.

2.     Load Data into a CASLib

Now that I have started my CAS session and have its UUID, I can load the table to CAS. Below is an example request for the table.loadTable CAS Action:


Authorization: Basic <Base-64EncodedCredentials>
 Content-Type: application/json



This request returns a log message: “NOTE: Cloud Analytic Services made the file <InputFilePathAndName> available as table <OutputTableName> in caslib <OutputCASLib>.”

For my example, I will load the SAS data set BASEBALL located in the helpdata CASLib to the Public CASLib and call the CAS Table SAS_BASEBALL.  I am copying the data to the Public CASLib to make it more readily available to all CAS users. Let’s first confirm that the SAS_BASEBALL table does not currently exist in the Public CASLib.

Public CASLib Before LoadTable CAS Action Called

I construct my request in HTTPRequestor as follows and submit the request:

Load Table Request/Response

Here is a screenshot of the raw transaction information.

Load Table Raw Transaction

Next, I will confirm that the SAS_BASEBALL data set is now loaded in the Public CASLib.

Public CASLib After LoadTable CAS Action Called

The SAS_BASEBALL data set is now available for use in applications such as SAS Visual Analytics and SAS Visual Data Builder.

3.     End CAS Session

Finally, I need to terminate my CAS Session. Below is an example request for the session.endSession CAS Action:

POST https://&lt;YourCASServer:Port&gt;/cas/sessions/&lt;CASSessionUUID&gt;/actions/session.endSession

Authorization: Basic &lt;Base-64EncodedCredentials&gt;
 Content-Type: application/json



This request returns a status of 0 indicating there was no error and the CASSessionUUID specified in the request has ended.

I construct my request in HTTPRequestor as follows and submit the request:

End CAS Session Request/Response

Here is a screenshot of the raw transaction information.

End CAS Session Raw Transaction


These calls can be strung together so you could schedule their execution. For more information on SAS Viya and REST APIs, refer to the following documentation the SAS Cloud Analytics REST API documentation.

Load Data into SAS Viya via REST API was published on SAS Users.

8月 152017

CAS data modelingThe CAS physical data model, i.e.what features CAS offers for data storage, and how to use them to maximize performance in CAS (and consequently SAS Visual Analytics 8.1 too).

So, specifically let’s answer the question:

What CAS physical table storage features can we use to get better performance in CAS and SAS Visual Analytics/CAS?

CAS Physical Table Storage Features

The following data storage features affect how CAS tables are physically structured:

  • Compression
  • Partitioning
  • Sorting
  • Repeated Tables
  • Extended Data Types (Varchar)
  • User Defined Formats

Compression — the Storage Option that Degrades Performance

data public.MegaCorp (compress=yes);
   set baselib.MegaCorp;

Partitioning and Sorting

Partitioning is a powerful tool for improving Bar Charts, Decision Tree, Linear Regression) provide grouping as well as classification functionality.

When performing analyses/processing, CAS first groups the data into the required BY-groups. Pre-partitioning on commonly-used BY-groups means CAS can skip this step, vastly improving performance.

Within partitions, tables can be sorted by non-partition-key variables. Pre-sorting by natural ordering variables (e.g. time) allows CAS to skip the ordering step in many cases just like partitioning allows CAS to skip the grouping step.

For a full use-case, consider a line graph that groups sales by region and plots by date. This graph object would benefit greatly from a CAS table that is pre-partitioned by region and pre-sorted by date.

Join Optimization

Partitioning can also support join operations since both the CAS FedSQL Merge Join algorithm utilize BY-GROUP operations to support their processing.

Pre-partitioning tables in anticipation of joins will greatly improve join performance. A good use case is partitioning both a large transaction table and an equally large reference table (e.g. an enormous Customer table) by the common field, customerID. When a DATA Step MERGE or a FedSQL join is performed between the two tables on that field, the join/merge will take advantage of partitioning for the BY-GROUP operation resulting in something similar to a partition-wise join.

Like Compression, partitioning and sorting can be implemented via CAS actions as well as data set options. Using the data set options is demonstrated below:

data mycas.bigOrderTable (partition=(region division) orderby=(year quarter month));
   set CASorBase.bigOrderTable;

Repeated Tables

By default, in distributed CAS Server deployments, CAS divides incoming tables into blocks and distributes those blocks among its DUPLICATE data set option or the Repeated Tables have two main use-cases in CAS:

1.     Join Optimization
2.     Small Table Operation Optimization

Join Optimization

For join operations, the default data distribution scheme can result in significant network traffic as matching records from the two tables travel between worker nodes to meet. If one of the two tables was created with the DUPLICATE/REPEAT option, then every possible record from that table is available on every node to the other table. There is no need for any network traffic.

Small Table Operation Optimization

For small tables, even single table operations can perform better with repeated instead of divided distribution. LASR actually implemented the “High Volume Access to Smaller Tables” feature for the same reason. When a table is repeated, CAS runs any required operation on a single worker node against the full copy of the table that resides there, instead of distributing the work.

As stated, repeated tables can be implemented with the DUPLICATE data set option, it can also be implemented with the REPEAT option on the PROC CASUTIL LOAD statement. The CASUTIL method is shown below:

proc casutil ;
   load data=sashelp.prdsale outcaslib=”caspath”
           casout=”prdsale” replace REPEAT ;
quit ;

Extended Data Types (VARCHAR)

With Viya 3.2 comes SAS’ first widespread implementation of variable length character fields. While Base SAS offers variable length character fields through compression, Viya 3.2 is the first major SAS release to include a save storage space, it also improves performance by reducing the size of the record being processed. CAS, like any other processing engine, will process narrower records more quickly than wide records.

User Defined Formats

User defined formats (UDFs) exist in CAS in much the same way they do in Base SAS. Their primary function, of course, is to provide display formatting for raw data values. Think about a format for direction. The raw data might be: “E”, “W”, “N”, “S” while the corresponding format values might be “East”, “West”, “North”, “South.”

So how might user defined formats improve performance in CAS? The same way they do in Base SAS, and the same way that VARCHAR does, by reducing the size of the record that CAS has to process. Imagine replacing multiple 200 byte description fields with 1 byte codes. If you had 10 such fields, the record length would decrease 1990 bytes ((10 X 200) – 10). This is an extreme example but it illustrates the point: User defined formats can reduce the amount of data that CAS has to process and, consequently, will lead to performance gains.

CAS data modeling for performance was published on SAS Users.

7月 262017

In a previous blog, I describe how there are a few new features related to report and page prompts in SAS Visual Analytics 8.1; namely the ability to configure cascading prompts in VA 8.1: Cascading Prompts as Report and Page Prompts.

In this blog, I will cover how to configure prompts, either report, page, or report canvas prompts, that use different data sources.

Different Data Sources with overlapping data values

First, you must have two different data sources added to your Visual Analytics report. These data sources must have values that overlap that you wish to prompt on. All of the values do not need to map, but they must have some values in common if you wish to use a shared prompt.

In this example, we will prompt for Product Line. Let’s examine the column values:

I’ve color coded the values that I would like to map together. I see that the only values that match “out-of-the-box” is Game.

One work around to get all of the values to match will be to create a Custom Category and use that column for the mapping.

In a “real world” scenario, this may not be ideal. The cardinality of the two columns may be so large that you may have to go back to either the source data or ETL job to produce better matching values.

However, if you are using date columns as the mapping columns things are considerably easier as year, month, and quarter are standard values that match without extra steps.

Here is my new Custom Category that I will use for my mapping:

Here are my mappings now. I will be using Product Line (New) for the Insight Toys data source moving forward.

Add prompts

There are two different locations where you can add prompts, i.e. Control Objects, which means there are two different ways to configure prompts with different data sources:

1.     Report and Page Prompts

2.     Report Canvas Prompts

Report and Page Prompt configuration for different data sources

For this first example, I will configure a Button Bar object placed in the Page Prompt area to filter two different data sources. For the Button Bar’s Category Role, I will use the data source with the largest available selection, in this case, the Product Line (New) from Insight Toys.

Now let’s configure this button bar to filter both data sources. You must activate the button bar by clicking on it, then right-mouse click and select Edit data source mappings

Then you simply have to pick your source table’s column to map to your target table’s column.

That’s it. The mapping is complete. Here is what the report would look like with different selections made for the button bar. Notice, that since I used the Insight Toys data source for the Role assignment, and it has more values than available in the Mega Corp data. If a selection is made where nothing matches in Mega Corp, as in the Gift example, then the Mega Corp bar chart is blank.

Report Canvas Prompt configuration for different data sources

In this second example, I am going to use a List Control object within the report canvas to filter two different data sources. Again, I will use the Insight Toys’ Product Line (New) column as the List Role Category assignment since it has the most values.

Now to configure the list to filter both bar charts. Click on the list control object to activate the window. Then select the Actions pane, and use the Add button to select Add filter.

Then select both bar charts as the target of the filter Action.
Next, select the Map data option.

Select the source data’s column to map to the target data’s column. Use the + to add additional column mapping criteria.

Here is how the report would look with a few of the values selected from the list table. You can see how both Mega Corp and Insight Toys display overlapping values for Product Line but for any unique Product Lines, such as Gift, its values are only displayed on the Insight Toys bar chart.

Now you know how to configure your control objects for multiple data sources. This works no matter how many data sources you add to your report, simply use the Map data option and select the mappings between the source data and target data.

As I mentioned earlier, a frequently used application of mapping prompts for multiple data sources is for date columns. Here is a screenshot of one example using year and month. I also styled the button bar’s selected background and text color to coordinate with the graphs.


SAS Visual Analytics 8.1: Configuring prompts with different source data was published on SAS Users.

7月 102017

In SAS Viya 3.2, SAS Visual Data Builder provides a mechanism for performing simple, self-service data preparation tasks for SAS Visual Analytics or other applications. SAS Visual Data Builder is NOT an Extract, Transform and Load (ETL) or data quality tool. You may still need one of those tools to perform more complex data preparation.

SAS Visual Data Builder can perform the following tasks:

  • View table and column profiles – provides information on number rows and columns on the table, as well as standard and advanced metrics for the columns.
  • Perform data transformations – includes items such as joining tables, transposing columns, creating calculated columns, filtering data and splitting columns.
  • Create plans – a plan is a collection of data transformations (actions) performed on one or more tables.  Plans can be saved and executed again.

SAS Visual Data Builder

To access SAS Visual Data Builder from SAS Home, select ≡ > SAS Visual Data Builder from the menu.
Note: The user must belong to the pre-defined custom user group Data Builders to have permission to access the application.

For SAS Visual Data Builder, the user can select their preferred default start screen in their application Settings.

The options are:

  • Show welcome dialog.
  • Start with data.
  • Start with new plan.
  • Choose existing plan.

With the SAS Viya 3.2 release, SAS Visual Data Builder is now a separate application from Visual Analytics (VA). There is not a one-to-one mapping of the feature set in SAS 9.4: VA 7.3 Data Preparation to SAS Viya 3.2: SAS Visual Data Builder.

For more information on SAS Visual Data Builder refer to the SAS Viya 3.2: Visual Data Builder was published on SAS Users.

6月 302017

In this blog post I’d like to explore how to create a custom group in SAS Viya to restrict access to functionality. To illustrate my points, we will create a report developers custom group and ensure that only users of that group can create reports and analysis in SAS Visual Analytics.

What a user or group can do (and see) is controlled by rules. A rule is a composite of authorization elements including:

  • Principal: user or group.
  • Target: a resource for example a service, folder or report.
  • Permissions: type of access for example read or write.
  • Setting: indication of whether access is provided, for example grant or prohibit.

The target of a rule is identified using a uniform resource identifier (uri). The uri can represent a folder, content such as a report or data plan, or functionality and features such as being able to import data. Here are some examples of uri’s in SAS Viya:

  • Data Plan: /dataPreparationPlans/plans/810e2c6b-4733-4d53-94fd-dfeb4df0de9e
  • Folder: /folders/folders/e28e35af-2673-4fc7-81fa-1a074f4c0de9
  • Functionality: /SASVisualAnalytics/**

In our example, we will look at restricting access SAS Visual Analytics for a subset of users. In SAS 9.4 this would have been accomplished using roles and capabilities. In SAS Viya, we will:

  • Create a custom group.
  • Govern that groups access to functionality using rules.

Create a New Custom Group

In SAS Environment Manager, as an administrator (only administrators can manage users and groups) select Users > Custom Groups > New.

In the new custom group screen give the group a name, a unique id and a description. We will call our group Report Developers.

After the new group is created, click the edit button to add new members to the group. You can add users or other groups as members of the new group.

Change the Rules so that Only Report Developers can Access the SAS Visual Analytics Application

Now that we have a new group called Report Developers, the next step is to create or update the rule that determines who can access this functionality. First, we will look at what rules currently apply to SAS Visual Analytics.

In SAS Environment Manager select the Security menu item and select the Rules view.

Select Filter by: ObjectURI and enter SASVisualA in the search box.

The second rule listed is the one we are interested in. Notice that URI ends with /**.  URI’s can end with /* or  / **.  An objectUri that includes the /** suffix affects access to all descendant functionality. For example, the /SASVisualAnalytics/** means all functionality in the SAS Visual Analytics application.

Select /SASVisualAnalytics/** and click the Edit icon.  The attributes show that this rule determines who can use SAS Visual Analytics. Currently you’ll see:

  • Grants Read access
    • to /SASVisualAnalytics/** and all its descendent functionality
      • to all authenticated users.

The rule works because the general authorization system implicitly disallows any access that is not granted. The current rule overrides the implicit deny to allow authenticated users to access SAS Visual Analytics. We will edit the rule and change the principal from Authenticated Users to ReportDevelopers.

In the edit rule screen under Principal, select ReportDevelopers.

The impact of the change is that now only users who are members of the Report Developers group can access the Visual Analytics application to create reports.

To test this, you can logon as a user who is not a member of the group. Those users will be able to navigate to reports and open then using the report viewer, but they will not be able to access SAS Visual Analytics to create new reports.

That is a quick look at using custom groups and rules to dictate what users can do in SAS Viya. There is much more detail on these topics in the SAS® Viya 3.2 Administration Guide:

New rules for authorization in SAS Viya was published on SAS Users.

6月 292017

In my last blog, we examined the data pane in SAS Visual Analytics 8.1. That blog discussed how to have the data pane display the data items of your active data source, and how to perform tasks such as viewing measure details, changing data item properties, and creating geographic data items, hierarchies, and custom categories.  In this blog, we’ll look at creating new calculated data items and calculated aggregations.

If you recall, l you display the Data pane in the Visual Analytics interface by clicking the Data icon on the left menu.

A calculated data item is a new data item created from existing data by using an expression.

  • Calculations are performed on un-aggregated data—the expression is evaluated on each row before aggregations are calculated.
  • Calculated data items can accept parameters.
  • A hierarchy can contain calculated category data items.
  • Calculated data items can be changed to geography data items and used in geo maps.

You can create a derived calculation from a category or measure data item by right-clicking on the data item and selecting Create calculation from data item.

For a category data item, you can create a distinct count, count, or number missing. Creating a derived calculation from a category data item:

For a measure data item, you can create a percent of total, or a periodic calculation based on one of your date data items. Creating a derived calculation from a measure data item:

Notice that in both cases, the new data item is an aggregation, so the new item will appear under the Aggregated Measure category in the data pane.

Note:  In order to use the periodic calculation types, your selected data item must include the year.

You can also edit these new data items by right-clicking on the data item and selecting Edit. Editing a derived calculation:

There is now a single interface for creating calculated data items of type Numeric, Character, Date or Datetime or Aggregated measures.

  • This interface provides both Visual mode and Text mode for viewing and editing the expression.
  • You can drag and drop data items or parameters and operators onto the expression in either mode.
  • In text mode, you can also type in your expression.

Creating a calculated data item or aggregated measure:

Specifying the calculation result type and format:

Some notes for using operators in calculations and aggregations:

  • Operators are provided for both calculations and aggregations.
  • You can expand and collapse each category of operators.
  • If you add an Aggregated operator to an expression, the result type will be changed to Aggregated Measure.
  • You cannot have nested aggregations in an expression.You also have access to periodic operators and simple and advanced aggregated operators for calculation aggregations.

In the same interface, you have access to simple and advanced numeric operators, simple and advanced text operators, along with boolean, date and time, and comparison operators for your calculations.

You also have access to periodic operators and simple and advanced aggregated operators for calculation aggregations.

The most important point to remember in using this interface is to think ahead as to whether you are creating a calculation (operating on each row) or an aggregation (operating across rows) and specify the data type and format before you begin to drag and drop data items and operators.  The default data type is Numeric, but if you add an aggregation operator, the type will automatically switch to Aggregated Measure.

Remember that you also create calculated items of character, date, and datetime data types–and you can choose from a list of date and datetime formats for those data types.

The SAS Visual Analytics 8.1 Data Pane: Creating Calculations and Aggregations was published on SAS Users.

6月 142017

In SAS Viya 3.2, the Self-Service Import provides a mechanism for a user to import (copy) data into the SAS Cloud Analytic Services (CAS) environment. The data is copied as a .sashdat file into the selected CAS Library location when it is imported.  Self-Service Import data can only be imported into CAS libraries of type PATH, HDFS, or DNFS.

The Self-Service Import functionality is available in the following applications:

  • SAS Visual Data Builder
  • SAS Visual Analytics
  • SAS Environment Manager – Data

To have access to Self-Service Import, the end user must be granted the Read permission on the /casManagement_capabilities/importData object URI in the Security ⇨ Rules area of SAS Environment Manager.

Self-Service Import supports importing data to CAS from Local, Server, and Social Media sources.

Self-Service Import in SAS Viya

SAS Viya 3.2: Self-Service Import


Local file data can be imported from Microsoft Excel (.XLSX or .XLS), text file (.TXT or .CSV), the clipboard, or a SAS Data Set (SASHDAT or SAS7BDAT). The file(s) must exist on a file system available to your PC.


After providing the appropriate server connection information, a table from LASR or select database types can be imported. The currently supported database types are:  Oracle, Teradata, Hadoop, PostgreSQL, and Impala. The Server selections displayed are dependent on your licensing and configuration.

Social Media

After authentication with the social media provider (Twitter, Facebook, Google Analytics, or YouTube), data can be imported through the social media provider’s public API. Access to these APIs is subject to the social media provider’s applicable license terms, terms of use, and other usage terms and policies.

Currently, there is a size limit for file imports that is set on the CAS Management service Configuration screen in SAS Environment Manager. The default size is 4GB. The local file importer has a 4GB limit because that is what the smallest size limit browser (Internet Explorer) is restricted to; however, Chrome and other browsers will allow larger file sizes, which is why there is a property that allows an Admin to set a higher limit. A modification to the max-file-size property requires a restart of the casManagement service.

Social Media and DBMS importers have no explicit limits. However, there is a limitation of the disk size of where casManagement is running because the uploaded file gets written to a temporary file on the server relative to casManagement.

For more information refer to the Self-Service Import section of the The Self-Service Import in SAS Viya 3.2 was published on SAS Users.

6月 052017

Refining your data for effective reports is even easier in the 8.1 release of SAS Visual Analytics. In this blog post, I’ll take a look at the data pane, how it displays data from your active data source, and a few tasks that you might want to perform, such as viewing measure details, changing data item properties, and creating geographic data items, hierarchies, and custom categories.  In a future blog, I’ll look at creating filters, new calculated data items, and calculated aggregations.

In the SAS Visual Analytics interface, you can display the Data pane by clicking the Data icon on the left menu.

Measure details

You can view data item properties and make these changes:

  • The name of a data item.
  • The Classification of Measure or Category data item.
  • The format of a Measure or Date/Time/Datetime data item.
  • The aggregation of a Measure data item.
  • Note:  User-defined formats for Category data items are honored, but cannot be changed.  The user-defined format must be available to the CAS server where the data is loaded.

A Measure classification can be changed to Category or Geography. A Category classification can be changed to Geography.  Date and Tim classifications cannot be changed.

You can modify the aggregation for a Measure data item:

You can modify measure formats:

  • You can expand to display available Duration and Currency formats.
  • Over thirty different Currency formats are available for local or international currency.  (Example: $56,790 or USD56,789)

Geography data items identity a geographic region or location, and are typically used to visualize data on a geographic map.

  • You can create geography data items by using predefined geography classifications such as countries or states.
  • You can create a custom geographic classification by providing latitude and longitude coordinates in your data source.
  • For predefined classifications, the values of your category data items must match the lookup values documented here.

Designating a Geography data item:

Designating a custom Geography data item:

A hierarchy enables you to add drill-down functionality to a report.

  • A hierarchy can display information from general to specific.
  • You can create category, date/datetime, or geography hierarchies.
  • Not all report objects support all types of hierarchies.

  • A custom category is a category data item which associates a set of alphanumeric values with intervals, ranges, or specific values of a data item.
  • A custom category can be based on a category or a measure data item.
  • A custom category can provide functionality in a report similar to that of a user-defined format—without having to have a format previously associated with the data item.

1-20 = ‘First group’
21-30 = ‘Second group’
31-40 = ‘Third group’

Depending on the report object, some roles require only one value; other roles may require multiple values.

You can right-click on a data item in the Roles pane to remove the data item from a role.

Duplicating a data item can enable you to display data in two different ways.

Duplicating the Date data item with 939 different values can enable you to create a report that analyzes production on each day of the week: Monday, Tuesday, Wednesday,…

Duplicating a measure data item can enable you to use the column as a category data item in reports as well.

Note: You can only delete data items that you have created, such duplicated data items or calculated data items.  Deleting a data item means that it no longer appears in the data pane.

This covers many of the basic tasks that you can complete in the new data pane. In my next blog, I’ll take a look at the visual and text editors for creating filter expressions and calculated items and aggregations in the data pane.

The new Data Pane in SAS Visual Analytics - It's painless! was published on SAS Users.