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Cindy Puryear 0
The Most Unusual Way You’ve Learned JMP

How do you learn best? In your sleep, when the unconscious mind is most receptive to suggestions? Calling to the “powers that be” for one of those “aha” moments when everything just sinks in? Swearing to your parents that you were actually studying when you came up with this plan?

Dylan Jones 0
Lack of knowledge and the root-cause myth

A lot of data quality projects kick off in the quest for root-cause discovery. Sometimes they’ll get lucky and find a coding error or some data entry ‘finger flubs’ that are the culprit. Of course, data quality tools can help a great deal in speeding up this process by automating

Arun C. Murthy 0
SAS high-performance capabilities with Hadoop YARN

For Hadoop to be successful as part of the modern data architecture, it needs to integrate with existing tools. This integration allows you to reuse existing resources (licenses and personnel) and is typically 60% of the evaluation criteria for integration of Hadoop into the data center. One of the most

Paul Kent 0
Share your cluster – How Apache Hadoop YARN helps SAS

Even though it sounds like something you hear on a Montessori school playground, this theme “Share your cluster” echoes across many modern Apache Hadoop deployments. Data architects are plotting to assemble all their big data in one system – something that is now achievable thanks to the economics of modern

Jim Harris 0
Data science versus narrative psychology

My previous post explained how confirmation bias can prevent you from behaving like the natural data scientist you like to imagine you are by driving your decision making toward data that confirms your existing beliefs. This post tells the story of another cognitive bias that works against data science. Consider the following scenario: Company-wide

Rick Wicklin 0
Creating heat maps in SAS/IML

In a previous blog post, I showed how to use the graph template language (GTL) in SAS to create heat maps with a continuous color ramp. SAS/IML 13.1 includes the HEATMAPCONT subroutine, which makes it easy to create heat maps with continuous color ramps from SAS/IML matrices. Typical usage includes

Data Visualization
Falko Schulz 0
Path analysis with SAS Visual Analytics

Introduction Understanding the behavior of your customers is key to improving and maintaining revenue streams. It is a an important part when crafting successful marketing campaigns. With SAS Visual Analytics 7.1 you can analyze, explore and visualize user behavior, click paths and other event-based scenarios. Monitoring the customer journey by visualizing

Rick Wicklin 0
Creating a basic heat map in SAS

Heat maps have many uses. In a previous article, I showed how to use heat maps with a discrete color ramp to visualize matrices that have a small number of unique values, such as certain covariance matrices and sparse matrices. You can also use heat maps with a continuous color

Jim Harris 0
Can data change an already made up mind?

Nowadays we hear a lot about how important it is that we are data-driven in our decision-making. We also hear a lot of criticism aimed at those that are driven more by intuition than data. Like most things in life, however, there’s a big difference between theory and practice. It’s

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