Data Visualization

11月 092018
 

In parts one and two of this blog posting series, we introduced machine learning models and the complexity that comes along with their extraordinary predictive abilities. Following this, we defined interpretability within machine learning, made the case for why we need it, and where it applies. In part three of [...]

SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 3] was published on Customer Intelligence Blog.

11月 092018
 

In parts one and two of this blog posting series, we introduced machine learning models and the complexity that comes along with their extraordinary predictive abilities. Following this, we defined interpretability within machine learning, made the case for why we need it, and where it applies. In part three of [...]

SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 3] was published on Customer Intelligence Blog.

11月 052018
 

In part one of this blog posting series, we introduced machine learning models as a multifaceted and evolving topic. The complexity that gives extraordinary predictive abilities also makes these models challenging to understand. They generally don’t provide a clear explanation, and brands experimenting with machine learning are questioning whether they [...]

SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 2] was published on Customer Intelligence Blog.

11月 012018
 

As machine learning takes its place in numerous advances within the marketing ecosystem, the interpretability of these modernized algorithmic approaches grows in importance. According to my SAS peer Ilknur Kaynar Kabul: We are surrounded with applications powered by machine learning, and we’re personally affected by the decisions made by machines [...]

SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 1] was published on Customer Intelligence Blog.

9月 112018
 

The data I was analyzing was about “trust.” Maybe that’s what got me thinking about Stephen Sondheim, the Broadway composer and lyricist of musicals like Sunday in the Park with George and Into the Woods and the lyricist for West Side Story. Trust is a heavy emotional topic.  Developmental psychologists [...]

Data visualization, the musical was published on SAS Voices by Elliot Inman

8月 222018
 

As a fun side project I recently looked into alternative visualization techniques in order to use computers to create art. An interesting approach is pointillism, which, according to Wikipedia is a "technique of painting in which small, distinct dots of color are applied in patterns to form an image." This [...]

Pointillistic art with SAS® Visual Analytics was published on SAS Voices by Falko Schulz

8月 022018
 

Recently, Scott Jackson, Director Business Intelligence at the University of North Carolina at Chapel Hill shared their data quality, reporting and analytics journey. They're using SAS in a multitude of ways – from operations, institutional research, athletics – and are now looking to scale to the enterprise. They've been so successful [...]

Scaling data and analytics across the University of North Carolina was published on SAS Voices by Georgia Mariani

6月 282018
 

We hear a lot about how various industries are using data visualization and analytics. But what about the education industry? The institutional research office (IR) at universities is the center for data, reports and analytics and provides decision makers with information about the university. The IR teams are working on [...]

How are data visualization and analytics used in higher education? was published on SAS Voices by Georgia Mariani

6月 202018
 

Regardless of industry, it has become a frequent occurrence that behind every data-driven marketer is an analytical ninja. Together, they formulate recipes in addressing the customer-centric paradigm that considers the different actions that a brand can take for a specific individual, and decides on the “best” one. The goal of [...]

SAS Customer Intelligence 360: Predictive next best actions was published on Customer Intelligence Blog.

6月 142018
 

In SAS Visual Analytics 8.2 on SAS Viya 3.3, there are a number of new data features available. Some of these features are completely new, and some are features from the 7.x release that had not yet been included in the 8.1 release.  I’ll cover a few of these new features in this post.

First of all, the Data pane interface has changed to enable users to access actions via fewer and better organized menus.

Data item properties can also be displayed for viewing or editing with a single click.

The new Change data source action displays a Repair report window if report data items are not in the new data source.  The window enables you to replace the missing data items with replacement data items from the new data source before continuing with the change.

Speaking of mapping, in SAS Visual Analytics 8.2, linked selections and filters can automatically be add to objects, and the objects may use different data sources. In that case, you can manually map data sources from the data pane.  The + icon enables you to add additional pairs of mappings.

When you create a new Geography data item in SAS Visual Analytics 8.2, in addition to using Predefined names and codes or your own custom latitude and longitude data items, you can now also use custom polygon shapes to display your own custom regions. Once you select Custom polygon shapes, you specify, in additional dialogs, the characteristics of your polygon provider.  You can use a CAS table or an Esri Feature Service.

For more information on custom polygons, see my previous blog here.

If you need to use and Esri shape file for your polygon data, there are macros available in VA 8.2 to convert the data to a SAS dataset and to load the data into CAS.

  • %SHPCNTNT display the contents of the shape file
  • %SHPIMPRT converts the shapefile into a SAS dataset and loads it into CAS.

The Custom Sort feature is also back in SAS Visual Analytics 8.2. Just right-click the data item, select Custom sort, and then select and order your data values.

For creating a new derived data item, there are several new calculations available for measures:

And speaking of creating calculated data items, you’ll want to check out three useful new operators that are available in SAS Visual Analytics 8.2:

A look at the new data pane and data item features in SAS Visual Analytics 8.2 was published on SAS Users.