Whether it is through your research, projects you tackle or by teaching, you work hard to accomplish your goals and that deserves recognition. At SAS, we support students and lecturers who want to make an impact in their careers by given them the opportunity to attend and present at an [...]
The post Students and professors earn recognition for their work at SAS Global Forum appeared first on SAS Analytics U Blog.
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.
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.
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.
The opening day of the conference brought this question:
Day two featured this question:
Finally, day three, and this question:
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.
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.
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:
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."
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
../deploywiz/sas.svc.connection.jar ..deploywiz/log4j.jar ../deploywiz/sas.security.sspi.jar ../deploywiz/sas.core.jar
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!
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.
“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
“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
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.
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:
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.”
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:
“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.”
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.
“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.
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.
“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.
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
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