sas global forum

4月 212017
 

Jess Ekstrom is an inspiration. When she was a sophomore in college at NC State University, Ekstrom interned at Disney World with the Make-A-Wish Foundation. One child in particular touched her life forever. Renee had brain cancer. Her family found out right before they were headed to Disney World to [...]

The post Finding meaning in the moment appeared first on SAS Analytics U Blog.

4月 182017
 

Ok, so you know how to create multiple sheets in Excel, but can anyone tell me how to control the name of the sheets when they are all created at once? In the ODS destination for Excel, the suboption SHEET_INTERVAL is set to TABLE by default.  So what does that [...]

The post How to control the name of Excel sheets when they are all created at once appeared first on SAS Learning Post.

4月 182017
 

In addition to his day job as Chief Technology Officer at SAS, Oliver Schabenberger is a committed lifelong learner. During his opening remarks for the SAS Technology Connection at SAS Global Forum 2017, Schabenberger confessed to having a persistent nervous curiosity, and insisted that he’s “learning every day.” And, he encouraged attendees to do the same, officially proclaiming lifelong learning as a primary theme of the conference and announcing a social media campaign to explore the issue with attendees.

This theme of lifelong learning served a backdrop – figuratively at first, literally once the conference began! – when Schabenberger, R&D Vice President Oita Coleman and Senior R&D Project Manager Lisa Morton sat down earlier this year to determine the focus for the Catalyst Café at SAS Global Forum 2017.

A centerpiece of SAS Global Forum’s Quad area, the Catalyst Café is an interactive space for attendees to try out new SAS technology and provide SAS R&D with insight to help guide future software development. At its core, the Catalyst Café is an incubator for innovation, making it the perfect place to highlight the power of learning.

After consulting with SAS Social Media Manager Kirsten Hamstra and her team, Schabenberger, Coleman and Morton decided to explore the theme by asking three questions related to lifelong learning, one a day during each day of the conference. Attendees, and others following the conference via social media channels, would respond using the hashtag #lifelearner. Morton then visualized the responses on a 13-foot-long by 8-foot-high wall, appropriately titled the Social Listening Mural, for all to enjoy during the event.

Questions for a #lifelearner

The opening day of the conference brought this question:

Day two featured this question:

Finally, day three, and this question:

"Committed to lifelong learning"

Hamstra said the response from the SAS community was overwhelming, with hundreds of individuals contributing.

Morton working on the Social Listening Mural at the SAS Global Forum Catalyst Café

“It was so interesting to see what people shared as their first jobs,” said Morton. “One started out as a bus boy and ended up a CEO, another went from stocking shelves to analytical consulting, and a couple said they immediately started their analytical careers by becoming data analysts right out of school.”

The “what do you want to learn next?” question brought some interesting responses as well. While many respondents cited topics you’d expect from a technically-inclined crowd – things like SAS Viya, the Go Programming Language and SASPy – others said they wanted to learn Italian, how to design websites or teach kids how to play soccer.

Morton said the connections that were made during the process was fascinating and made the creation of the mural so simple and inspiring. “The project showed me how incredibly diverse our SAS users are and what a wide variety of backgrounds and interests they have.”

In the end, Morton said she learned one thing for sure about SAS users: “It’s clear our users are just as committed to lifelong learning as we are here at SAS!”

My guess is that wherever you’ll find Schabenberger at this moment – writing code in his office, behind a book at the campus library, or discussing AI with Dr. Goodnight – he’s nodding in agreement.

The final product

Nurturing the #lifelearner in all of us was published on SAS Users.

4月 092017
 

Thanks to a new open source project from SAS, Python coders can now bring the power of SAS into their Python scripts. The project is SASPy, and it's available on the SAS Software GitHub. It works with SAS 9.4 and higher, and requires Python 3.x.

I spoke with Jared Dean about the SASPy project. Jared is a Principal Data Scientist at SAS and one of the lead developers on SASPy and a related project called Pipefitter. Here's a video of our conversation, which includes an interactive demo. Jared is obviously pretty excited about the whole thing.

Use SAS like a Python coder

SASPy brings a "Python-ic" sensibility to this approach for using SAS. That means that all of your access to SAS data and methods are surfaced using objects and syntax that are familiar to Python users. This includes the ability to exchange data via pandas, the ubiquitous Python data analysis framework. And even the native SAS objects are accessed in a very "pandas-like" way.

import saspy
import pandas as pd
sas = saspy.SASsession(cfgname='winlocal')
cars = sas.sasdata("CARS","SASHELP")
cars.describe()

The output is what you expect from pandas...but with statistics that SAS users are accustomed to. PROC MEANS anyone?

In[3]: cars.describe()
Out[3]: 
       Variable Label    N  NMiss   Median          Mean        StdDev  
0         MSRP     .   428      0  27635.0  32774.855140  19431.716674   
1      Invoice     .   428      0  25294.5  30014.700935  17642.117750   
2   EngineSize     .   428      0      3.0      3.196729      1.108595   
3    Cylinders     .   426      2      6.0      5.807512      1.558443   
4   Horsepower     .   428      0    210.0    215.885514     71.836032   
5     MPG_City     .   428      0     19.0     20.060748      5.238218   
6  MPG_Highway     .   428      0     26.0     26.843458      5.741201   
7       Weight     .   428      0   3474.5   3577.953271    758.983215   
8    Wheelbase     .   428      0    107.0    108.154206      8.311813   
9       Length     .   428      0    187.0    186.362150     14.357991   

       Min       P25      P50      P75       Max  
0  10280.0  20329.50  27635.0  39215.0  192465.0  
1   9875.0  18851.00  25294.5  35732.5  173560.0  
2      1.3      2.35      3.0      3.9       8.3  
3      3.0      4.00      6.0      6.0      12.0  
4     73.0    165.00    210.0    255.0     500.0  
5     10.0     17.00     19.0     21.5      60.0  
6     12.0     24.00     26.0     29.0      66.0  
7   1850.0   3103.00   3474.5   3978.5    7190.0  
8     89.0    103.00    107.0    112.0     144.0  
9    143.0    178.00    187.0    194.0     238.0  

SASPy also provides high-level Python objects for the most popular and powerful SAS procedures. These are organized by SAS product, such as SAS/STAT, SAS/ETS and so on. To explore, issue a dir() command on your SAS session object. In this example, I've created a sasstat object and I used dot<TAB> to list the available SAS analyses:

SAS/STAT object in SASPy

The SAS Pipefitter project extends the SASPy project by providing access to advanced analytics and machine learning algorithms. In our video interview, Jared presents a cool example of a decision tree applied to the passenger survival factors on the Titanic. It's powered by PROC HPSPLIT behind the scenes, but Python users don't need to know all of that "inside baseball."

Installing SASPy and getting started

Like most things Python, installing the SASPy package is simple. You can use the pip installation manager to fetch the latest version:

pip install saspy

However, since you need to connect to a SAS session to get to the SAS goodness, you will need some additional files to broker that connection. Most notably, you need a few Java jar files that SAS provides. You can find these in the SAS Deployment Manager folder for your SAS installation:
../deploywiz/sas.svc.connection.jar
..deploywiz/log4j.jar
../deploywiz/sas.security.sspi.jar
../deploywiz/sas.core.jar

The jar files are compatible between Windows and Unix, so if you find them in a Unix SAS install you can still copy them to your Python Windows client. You'll need to modify the sascgf.py file (installed with the SASPy package) to point to where you've stashed these. If using local SAS on Windows, you also need to make sure that the sspiauth.dll is in your Windows system PATH. The easiest method to add SASHOMESASFoundation9.4coresasexe to your system PATH variable.

All of this is documented in the "Installation and Configuration" section of the project documentation. The connectivity options support an impressively diverse set of SAS configs: Windows, Unix, SAS Grid Computing, and even SAS on the mainframe!

Download, comment, contribute

SASPy is an open source project, and all of the Python code is available for your inspection and improvement. The developers at SAS welcome you to give it a try and enter issues when you see something that needs to be improved. And if you're a hotshot Python coder, feel free to fork the project and issue a pull request with your suggested changes!

The post Introducing SASPy: Use Python code to access SAS appeared first on The SAS Dummy.

4月 072017
 

“This conference has been one of my best because I’ve learned about GatherIQ, a social, good cause initiative that’s made me think about the bigger picture, and how I can help people who need help,” said a SAS Global Forum attendee who heard about SAS’ new data-for-good crowdsourcing app at [...]

Using data for good with GatherIQ was published on SAS Voices by Becky Graebe

4月 072017
 

“This conference has been one of my best because I’ve learned about GatherIQ, a social, good cause initiative that’s made me think about the bigger picture, and how I can help people who need help,” said a SAS Global Forum attendee who heard about SAS’ new data-for-good crowdsourcing app at [...]

Using data for good with GatherIQ was published on SAS Voices by Becky Graebe

4月 052017
 

Emma Warrillow, President of Data Insight Group, Inc., believes analysts add business value when they ask questions of the business, the data and the approach. “Don’t be an order taker,” she said.

Emma Warrillow at SAS Global Forum.

Warrillow held to her promise that attendees wouldn’t see a stitch of SAS programming code in her session Monday, April 3, at SAS Global Forum.

Not that she doesn’t believe programming skills and SAS Certifications aren’t important. She does.

Why you need communication skills

But Warrillow believes that as technology takes on more of the heavy lifting from the analysis side, communication skills, interpretation skills and storytelling skills are quickly becoming the data analyst’s magic wand.

Warrillow likened it to the centuries-old question: If a tree falls in a forest, and no one is around to hear it, did it make a sound? “If you have a great analysis, but no one gets it or takes action, was it really a great analysis?” she asked.


If you have a great analysis, but no one gets it or takes action, was it really a great analysis?
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To create real business value and be the unicorn – that rare breed of marketing technologist who understands both marketing and marketing technology – analysts have to understand the business and its goals and operations.

She offered several actionable tips to help make the transition, including:

1. Never just send the spreadsheet.

Or the PowerPoint or the email. “The recipient might ignore it, get frustrated or, worse yet, misinterpret it,” she said. “Instead, communicate what you’ve seen in the analysis.”

2. Be a POET.

Warrillow is a huge fan of the work of Laura Warren of Storylytics.ca. who recommends an acronym approach to data-based storytelling and making sure every presentation offers:

  • Purpose: The purpose of this chart is to …
  • Observation: To illustrate that …
  • Explanation: What this means to us is …
  • Take-away or Transition: As a next step, we recommend …

3. Brand your work.

“Many of us suffer from a lack of profile in our organizations,” she said. “Take a lesson from public relations and brand yourselves. Just make sure you’re a brand people can trust. Have checks and balances in place to make sure your data is accurate.”

4. Don’t be an order taker.

Be consultative and remember that you are the expert when it comes to knowing how to structure the campaign modeling. It can be tough in some organizations, Warrillow admitted, but asking some questions and offering suggestions can be a great way to begin.

5. Tell the truth.

“Storytelling can be associated with big, tall tales,” she said. “You have to have stories that are compelling but also have truth and resonance.” One of her best resources is The Four Truths of the Storyteller” by Peter Gruber, which first appeared in Harvard Business Review December 2007.

6. Go higher.

Knowledge and comprehension are important, “but we need to start moving further up the chain,” Warrillow said. She used Bloom’s Taxonomy to describe the importance of making data move at the speed of business – getting people to take action by moving into application, analysis, synthesis and evaluation phases.

7. Prepare for the future.

“Don’t become the person who says, ‘I’m this kind of analyst,’” she said. “We need to explore new environments, prepare ourselves with great skills. In the short term, we’re going to need more programming skills. Over time, however, we’re going to need interpretation, communication and storytelling skills.” She encouraged attendees to answer the SAS Global Forum challenge of becoming a #LifeLearner.

For more from Warrillow, read the post, Making data personal: big data made small.

7 tips for becoming a data science unicorn was published on SAS Users.

4月 052017
 

In an industry full of word people, it's not uncommon to hear journalists lament, “Data, what are you doing here!?” But today, data is a tool in the newsroom, and reporters need to know how to analyze and present data to readers as part of their role in communicating information to the public. Amanda [...]

What can a BBC data journalist teach you about data visualization? was published on SAS Voices by Becky Graebe

4月 042017
 

Two minutes in, I knew the 2017 SAS Global Forum Technology Connection would be anything but typical or average. Maybe that’s because SAS’ Chief Technology Officer Oliver Schabenberger was running the show, and nothing he does is ever typical or average. His first surprise of the morning was his entrance. [...]

Impressive technology, surprising connections was published on SAS Voices by Marcie Montague

4月 032017
 

At Opening Session, SAS CEO Jim Goodnight and Alexa have a chat using the Amazon Echo and SAS Visual Analytics.

Unable to attend SAS Global Forum 2017 happening now in Orlando? We’ve got you covered! You can view live stream video from the conference, and check back here for important news from the conference, starting with the highlights from last night’s Opening Session.

While the location and record attendance made for a full house this year, CEO Jim Goodnight explained that there couldn’t be a more perfect setting to celebrate innovation than the world of Walt Disney. “Walt was a master innovator, combining art and science to create an entirely new way to make intelligent connections,” said Goodnight. “SAS is busy making another kind of intelligent connection – the kind made possible by data and analytics.”

It’s SAS’ mission to bring analytics everywhere and to make it ambient. That was exactly the motivation that drove SAS nearly four years ago when embarking on a massive undertaking known as SAS® Viya™. But SAS Viya – announced last year in Las Vegas – is more than just a fast, powerful, modernized analytics platform. Goodnight said it’s really the perfect marriage of science and art.

“Consider what would be possible if analytics could be brought into every moment and every place that data exists,” said Goodnight. “The opportunities are enormous, and like Walt Disney, it’s kind of fun to do the impossible.”

Driving an analytics economy

Executive Vice President and Chief Marketing Officer Randy Guard took the stage to update attendees on new releases available on SAS Viya and why SAS is so excited about it. And he explained the reason for SAS Viya comes from the changes being driven in the analytics marketplace. It’s what Guard referred to as an analytics economy – where the maturity of algorithms and techniques progress rapidly. “This is a place where disruption is normal, a place where you want to be the disruptor; you want to be the innovator,” said Guard. That’s exactly what you can achieve with SAS Viya.

As if SAS Viya didn’t leave enough of an impression, Guard took it one step further by inviting Goodnight back on stage to give users a preview into the newest innovation SAS has been cooking up. Using the Amazon Echo Dot – better known as Alexa – Goodnight put cognitive computing into action as he called up annual sales, forecasts and customer satisfaction reports in SAS® Visual Analytics.

Though still in its infant stages of development, the demo was just another reminder that when it comes to analytics, SAS never stops thinking of the next great thing.

AI: The illusion of intelligence

On his Segway, Executive Vice President and Chief Technology Officer Oliver Schabenberger talks AI at the SAS Global Forum Opening Session.

With his Segway Mini, Executive Vice President and Chief Technology Officer Oliver Schabenberger rolled on stage, fully trusting that his “smart legs” wouldn’t drive him off and into the audience. “I’ve accepted that algorithms and software have intelligence; I’ve accepted that they make decisions for us, but we still have choices,” said Schabenberger.

Diving into artificial intelligence, he explained that today’s algorithms operate with super-human abilities – they are reliable, repeatable and work around the clock without fatigue – yet they don’t behave like humans. And while the “AI” label is becoming trendy, true systems deserving of the AI title have two distinct things in common: they belong to the class of weak AI systems and they tend to be based on deep learning.

So, why are those distinctions important? Schabenberger explained that a weak AI system is trained to do one task only – the system driving an autonomous vehicle cannot operate the lighting in your home.

“SAS is very much engaged in weak AI, building cognitive systems into our software,” he said. “We are embedding learning and gamification into solutions and you can apply deep learning to text, images and time series.” Those cognitive systems are built into SAS Viya. And while they are powerful and great when they work, Schabenberger begged the question of whether or not they are truly intelligent.

Think about it. True intelligence requires some form of creativity, innovation and independent problem solving. The reality is, that today’s algorithms and software, no matter how smart, are being used as decision support systems to augment our own capabilities and make us better.

But it’s uncomfortable to think about fully trusting technology to make decisions on our behalf. “We make decisions based on reason, we use gut feeling and make split-second judgment calls based on incomplete information,” said Schabenberger. “How well do we expect machines to perform [in our place]when we let them loose and how quickly do we expect them to learn on the job?”

It’s those kinds of questions that prove that all we can handle today is the illusion of intelligence. “We want to get tricked by the machine in a clever way,” said Schabenberger. “The rest is just hype.”

Creating tomorrow‘s analytics leaders

With a room full of analytics leaders, Vice President of Sales Emily Baranello asked attendees to consider where the future leaders of analytics will come from. If you ask SAS, talent will be pulled from universities globally that have partnered with SAS to create 200 types of programs that teach today’s students how to work in SAS software. The commitment level to train up future leaders is evident and can be seen in SAS certifications, joint certificate programs and SAS’ track toward nearly 1 million downloads of SAS® Analytics U.

“SAS talent is continuing to building in the marketplace,” said Baranello. “Our goal is to bring analytics everywhere and we will continue to partner with universities to ready those students to be your successful employees.”

Using data for good

More than just analytics and technology, SAS’ brand is a representation of people who make the world a better place. Knowing that, SAS announced the development of GatherIQ – a customized crowdsourcing app that will begin with two International Organization for Migration (IMO) projects. One project will specifically focus on global migration, using data to keep migrants safe as they search for a better life. With GatherIQ, changing the world might be as easy as opening an app.

There's much more to come, so stay tuned to SAS blogs this week for the latest updates from SAS Global Forum!

SAS Viya, AI star at SAS Global Forum Opening Session was published on SAS Users.