How are analytics moving the world?

155786129Over the past few years, I’ve talked a lot about analytics culture. In speeches, in conversations with customers and even in posts on this blog, it’s a topic that comes up again and again: How do you create a culture that encourages analytical thinking and data driven decisions?

This is still an important topic, but I’ve noticed a lot of organizations are moving beyond that. They’re bought into the idea of analytics and they know the cultural issues are important, but now they want to hear examples. How are other businesses using analytics to move the world? And how can their ideas be applied across other industries?

As we move into October and finalize plans for this year’s Premier Business Leadership Series, I expect to have similar conversations. Executives at this event are well informed in terms of what data can bring to their businesses. Now they’re interested in hearing specific use cases, and they’ll find a lot of that in the conference agenda, especially in the sessions and workshops.

Whether you attend one of our conferences or network in our online communities, come with questions: What’s working? What’s not working? What’s making a difference? What projects are other people finding valuable? Are they industry specific? Or are they universal?

We hope you’ll find the answers to these and other questions – and that you find some inspiration too.

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Q4 2014 Intelligence Quarterly: Global citizenship and the role of technology

4Q 2014 Intelligence Quarterly: Journal of Advanced AnalyticsBusinesses taking action to expand and enrich their social responsibilities. Public sector agencies improving the lives of citizens. These are some of the stories I hear from customers and colleagues around the world that inspire me. And these are the stories I wish to share with you in the latest issue of Intelligence Quarterly – stories that bring to life the many ways analytics helps make our world a better place to live.

Turn on the news today, and – more often than not – you will hear stories of disease, abuse, poverty and war. The financial news is not much different, although the increasing use of behavioral economics offers some hope. When businesses can better understand – and meet – customer motives and expectations, everyone wins.

We often hear that growth is the answer to all our problems. However, growth alone will not suffice. As behavioral economics develop, we need “inclusive growth,” where everyone can play a part and all sectors can benefit.

We know a brighter future is possible for all. As the following stories illustrate, analytics is a powerful technology that can be used to improve our world. The global family needs us now more than ever, and technology has a role to play in global citizenship. Just consider:

  • In New Zealand, the Ministry of Social Development is using analytics as a tool for transformation, to help struggling young people create a better future. This is a perfect example of inclusive growth: It helps the individual, the society and the economy alike. What you'll learn: How better targeting empowers welfare beneficiaries with confidence and life skills, and reduces the cycle of long-term benefit dependency.
  • After Typhoon Haiyan devastated the Philippines, analytics helped aid workers prioritize assistance levels and supply distribution. What you'll learn: How the International Organization for Migration incorporated social media data with geographic and real-time data to find higher concentrations of diarrhea and fever, and to discover that the greatest needs in Guiuan were for antibiotics and fuel for hospital generators.
  • In France, job seekers who collect unemployment benefits are receiving assistance that is customized to their unique situations. What you'll learn: How analytics has helped empower local service branches to design personalized pathways to employment, helping them meet statewide quality and consistency standards and goals.
  • We've also included five inspiring examples of how health care organizations are changing the way we look at health on a global scale. One enables early intervention and reduces hospital stays for veterans in Australia. Another pools patient information worldwide to expedite medical research. And yet another has saved hundreds of lives in North Carolina thanks to analytics, with the potential to save even more.

Here at SAS, we are committed to helping organizations use data for good. Big data must be used to close the gap between perception and mathematical truth. And this can only be done with analytics.

Another way to become global citizens and agents of change in our communities is to spread the positive stories of disruptive technologies improving society.

To that end, our work here at SAS has never been more important. As we remain focused on our work at hand, I am confident that we will not only contribute to inclusive growth, but also to the role big data analytics will play in improving the lives of those around us.

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Five crucial behaviors of a true social business

463434385Social media has changed the way we consume and interact with information. It’s not just a change in the way we write and read using short bursts of information that match our attention spans. It’s also a change in the way we interact with brands online.

Consumers want to understand, from a storytelling perspective, the value a brand might bring to them. They’re not interested in getting pummeled with white papers and marketing materials alone. Instead, they’re interested in putting together their own story of what a company means to them, and sometimes even telling a piece of that story themselves.

What does this mean for brands? And how are we seeing it play out? It means that brands have to change the way they operate online, especially in the five areas I’ll cover here. 

1. Look at how you’re trending on social media channels

Social media gives you a daily pulse on how well your corporate values are perceived by people outside your organization. It offers an opportunity to react and change direction based on customer feedback. This represents the opportunity to tap into a focus group 24x7.

We ought to be paying attention. And we should be able to adjust our marketing mix and our messages in reaction to what we read, as opposed to launching marketing programs that are locked and loaded with very little opportunity for change.

2. Implement a monitoring and response plan

What are you doing in real time to respond on social media? Are you answering questions online? Sharing content that your audience asks for? Responding to requests for new features in your products? It’s not just about listening to what people are saying on Twitter. It’s also about responding quickly – and making sure the answers are coming from people in your organization with the domain knowledge to respond. You can’t expect an intern to answer complex questions about your products. Only the engineers and product managers can do that, so they need to be responding too.

3. Integrate social media into the fiber of the company

The future is having social media more deeply ingrained in more aspects within an organization, not just in the marketing function. I ought to be able to walk down the hallway at SAS and find anyone in Product Marketing or R&D and ask, “What did you see on social media today?” and not have them say, “Uhhhhhh ...”

As we look to build more of a social media culture at SAS, we’ve looked at everything from training to hiring practices. We ask, do we have people in place in every department who are embracing social media, and understand what it means and can put it into practice? Are we committed to keeping those people current?

During new employee orientation, for example, we don’t just say, “Here’s your badge, your phone, your desk and your computer.” Instead, we say, “Here’s our brand values, and here’s how you can participate with the external community.”

4. Loosen your standards around your brand image online

This is hard, but you have to let go of the fear of what people might say. When social media first became popular, people created all kinds of standards. Employees were told not to expose anything about the company or give anyone an opportunity to say something bad. Now, we’re more open. Brands are asking for feedback, and they’re open to hearing the good and the bad.

You need somebody who can establish standards and set guidelines so nobody strays too far off brand. At same time, the beauty of social media is trusting employees to represent your brand and let them loose. If you have the right people in place, you should give them leeway to participate.

It's important not to overreact to negative comments from critics who are often just looking for a reaction. We have some very loyal employees at SAS. If somebody sees something negative on social, people want to react, but you have to let these things play out. More often than not, the community will self-moderate, and your customer champions will come to your defense.

5. Develop a closed loop measurement system for social media

The marketer’s role has changed significantly in last five to seven years, and not just from a social media perspective – but from a digital and analytics perspective overall. Marketing has become much more of a science and less of what the Mad Men TV series portrays, where creative people drank scotch, scratched their heads and magically had an ad campaign.

Today, you can’t survive as a marketer without an understanding of technology, digital channels, social media – and how can you quantify it all. If you look at where we’re headed, a few organizations get it. A lot of organizations know it. But only a few have really put it into practice in a closed loop fashion. The brands that get it understand that social media is not just about listening and tweeting but also about measuring the impact of communications out in the market and then, based on that impact, refining how you communicate and how you do your business. If you can get that right, you will be a truly social organization.

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Big data benefits in the news

In my last post, I talked about big data blunders in the news. Today’s post is its opposite. It’s only fair to follow up that negative post with some positive stories about big data projects that offer real benefits to society.

There are many, many examples of big data being used for good in the world, but I’m sharing just a few recent favorites I’ve come across. These examples show how big data is being used to improve the world around us in big and small ways.

Big data predicts global conflicts: A researcher from Georgetown University has designed an open source tool that stores global event data and news stories since 1979. Predictive models applied to this data can detect when and where new conflicts might arise. 

Big data for cancer research: The Project Data Sphere initiative is an open data project that combines clincal trial data from multiple pharmaceutical companies to give researchers more insight into different therapies.  More than 10 companies are expected to participate, with a focus on open collaboration and discovering new cancer treatments.

Big data illuminates our understanding of the world: The Kaggle contest site has launched a new competition to analyze data from the ATLAS Experiment. The goal is to find new methods to identify the presence of Higgs Boson particles in millions of simulated collisions. You don’t have to be a particle physicist to play along … just an analyst with an idea or two. 

Big data assists with disaster recovery: In the Philippines, relief workers for the International Organization for Migration combined data from hundreds of displacement sites with public data sources, including social media data, to visualize and prioritize where to send assistance and aid.  As part of the project, text analyses of tweets indicated where aid was needed, what sites already had relief workers, and what specific items were needed most.

Big data eradicates pests: Scientists at Brigham Young University are simulating the locations of tsetse flies to help control efforts to eradicate the pests. Meanwhile, city officials in Chicago are using big data to prioritize efforts for exterminating rats in the city. Similar projects could be used to stop the spread of disease carrying creatures around the world.

A common thread you’ll notice in these stories is the use of open data or public data sources, which is where I see a lot of potential in the use of big data. Whether it’s telecom companies combing customer data to create more targeted offers or pharmaceutical companies combining data to develop cancer drugs faster, the point is that we can all see the benefits when data is shared responsibly.

What are your favorite stories about big data or open data being used to benefit society?

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Helping the academic community build an analytics army

For those of you who are classic rock fans, you may remember Alice Cooper’s title track “School’s Out for Summer” on the album “School’s Out.” That song captures students’ excitement of a taking a hiatus from the classroom. But for professors, summer is a time to continue their own education and gear up for the next semester.

As I mentioned in my last post about analytic talent, SAS is doing its part to address this need through a multi-pronged educational approach - including our latest Analytics U initiative, to bring SAS analytics into the hands of students, professors, and researchers. As part of that program, we are committed to not only provide free software, but also offer free summer workshops to help professors integrate the latest analytical techniques into their curricula.

Higher education connections
SAS has a long history with the academic community, starting as a project at North Carolina State University in the 1960s. So because of our roots, we understand the important role universities have in establishing the vital foundation of knowledge and experiences valued in today’s information economy. That’s why we are doing everything we can to facilitate the transfer of analytics knowledge in formats that make it as easy and headache-free as possible to professors.

Free data mining training for professors
Just a couple of weeks ago, we hosted a data mining workshop for a 110 professors from across the US. It was the biggest turnout in the 12-year history of this event. Our goal was to provide focused training on technology that they could quickly incorporate into their classes. We were extremely delighted with the turnout from more than 110 professors across the US at our Cary headquarters.

As is depicted in the video below, I am encouraged from the feedback we received from some of the attendees. I want to share a couple of them.


Frank Alt, Professor at University of Maryland at College Park, said, “For me to teach my students, I have to be on the cutting edge. SAS is putting me right on that frontier. I feel privileged to be here and take advantage of what SAS is offering.”

And recent feedback from Philip Ramsey, a faculty member in the Department of Mathematics and Statistics at the University of New Hampshire expressed the following, “I am writing to you to thank all of you and the SAS Institute for holding this event and to let you know that I found the workshop outstanding … My only complaint is that I wish the class had been 5 days instead of 3. For me personally the class was great fun and very educational.”

This feedback tells me that we are moving in the right direction to give professors the tools they need to integrate analytics training into their curricula. Their enthusiasm for analytics is exactly what we want to see transferred to their students.

Our long-term commitment to education
I’m also very proud of our collaborative efforts to build a strong contingent of analytics-savvy college graduates. We are serious about continuing to improve our outreach and stand by our pledge to work closely with academics to produce a robust pipeline of graduates who understand the value of analytics and are unafraid to apply it. I’m constantly encouraging our SAS employees to spread the word about our educational efforts.

I also want to ask those of you in the academic community to keep us informed of your needs and how we can support your efforts further. Together, our collaboration has limitless potential to produce a SAS army ready to conquer the data challenges ahead.

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Energized about energy

I’ve been told I have rocks for brains before, but right now I have rocks on the brain – the kind that are millions of years old and contain precious stores of oil and gas.


One reason I have petroleum on my mind is that I’ve just returned from Brazil, where the oil and gas industry is the largest contributor to the economy. Naturally, discussions around high-performance analytics and energy figured prominently in my meetings – that is, when we weren’t talking FIFA World Cup.

Another reason I’m energized about the topic is a recent glowing endorsement from Petrobras. The Brazilian energy giant has its sights set on total resource recovery – the ability to leave no stone unturned when it comes to finding and recovering oil and gas resources. To get there, they’re using SAS® Analytics to optimize the placement of wells and extend the life of mature fields.

And it’s working. Their senior geologist recently called SAS “100 percent reliable.” Now that’s a testimonial!

Companies like Petrobras need that kind of accuracy because they’re investing billions in their projects. They have to make smart decisions about where to look – and where not to look. When they get it right, the rewards are substantial. On average, Petrobras fields are producing 230,000 more barrels per day after using SAS.

That kind of success makes me happy. Wanting to learn more, I picked up Keith Holdaway’s new book, Harness Oil and Gas Big Data with Analytics. Among other things, it covers how geophysicists, geologists and petroleum engineers can come to view data as not a burden but a blessing – one that opens up entirely new vistas for the industry. Part of the reason the US recently overtook Saudi Arabia as the world’s largest producer of energy resources (namely gas) is that sources that had been nearly impossible to find or use are becoming much more accessible, thanks to the power of analytics.

But it isn’t just about finding oil and gas. It’s also about keeping the equipment running to pull the “black gold” out of the ground and get it on the path to consumers.

For example, steam-assisted gravity drainage is a revolutionary approach to extracting heavy and highly viscous oil from the ground. This horizontal drilling method works by using steam, gas and pressure levels that are optimized with analytical models. Analytics can also determine the optimal operational parameters that enable more efficient drilling and avoid costly downtime. Math plus heavy machinery: What’s cooler than that?

Analytics is also helping keep the industry safe. Predictive models allow engineers to see trouble brewing in pumps or refineries and address issues before they interfere with production. For example, Shell Exploration and Production is using SAS® Predictive Asset Maintenance to extend the lifespan of their equipment and prevent accidents. When the software alerts signal a performance problem, Shell can act quickly to prevent an upset.

The time and money saved allows Shell to do more exploration. (Learn more.)

From upstream exploration and production to the downstream applications of refining, logistics and retail, my friends in petroleum are getting smarter all the time about how to find the resource and get it into the tanks of consumers.

And I’m proud to say they’re doing it with the help of advanced analytics.

To learn more about the application of analytics to the oil and gas industry, read the SAS white paper.

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Big data blunders in the news

Facebook’s mood manipulation experiment is the latest big data blunder in the news. In 2012, the social networking site altered news feeds for thousands of users to display primarily positive or negative posts – and then watched to see if users’ posts reflected what they were seeing in their feeds.

I’m sure that most businesses go into these types of programs with good intentions – but the concerns of individuals about their privacy cannot be overlooked. The issues of data security and consumer privacy protection are age old problems that existed with small data too. With big data, however, we’re affecting a much larger population. The risk is greater, but if you can get the balance right, the rewards – for individuals and society - can be greater too.

What could businesses do differently to make their programs more successful?

  1. Make programs available only for those that opt in. If Facebook had said, “Do you want to take part in research projects to help us improve our experience with you?” plenty of people would have agreed to participate. Up front permission also means the results can be shared more openly, and the community feels invested enough to share the results and offer ideas on how to use the data to benefit users.
  2. Provide clear benefits to consumers. Research consistently shows that consumers are willing to share data if they receive something in return. The benefits could be discounts, improved personalization, service enhancements or even larger benefits to society. The catch is that you can’t just promise these things. Consumers have to experience the benefits themselves, or they will opt out of the service later.
  3. Communicate the purpose and limitations of the program. If businesses can present big data programs in a way that makes the benefits clear to shopper or users, then they will be embraced. Program limitations should also be explained up front in simple language so consumers know what to expect.

From providing better service bundles and offering relevant discounts to bringing new drugs to market and predicting economic trends, big data has the potential to provide many benefits. The majority of these programs should be about improving consumers’ experiences or improving society.

I’d love to see a news cycle that focuses on the benefits of big data, not just the blunders. If organizations focus on the three steps above, I’m confident we’ll be reading more and more of those types of positive stories, and we’ll all see benefits as a result.

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Q3 2014 Intelligence Quarterly: Accelerate innovation with big data analytics

IQ_3Q_2014_cover_internationalSince I started publishing this journal of case studies several years ago, I’ve always written about the transformative impact of big data analytics. I’ve been sharing best practices and industry insights, but I’m now often asked, how? How can organizations transform for tomorrow while still focusing on success today? How can employees stop wasting time on the old legacy systems and move to current and future states without running the risk of disruptions?

In this issue of Intelligence Quarterly, I’ve set out to answer that question – showing you how to leverage big data analytics to come out ahead, no matter what your legacy is.

With big data comes big challenges and even bigger opportunities. Social data, mobile data and sensor data are just a few of the newer data sources that – when properly analyzed – can help improve your business in many ways. Yet many organizations find themselves entangled with dysfunctional legacy systems that get in the way of innovation.

It’s true that technology is the foundation for and the driver of innovation, but just like weeds can choke out new grass, outdated technology can stifle innovation. When you develop a culture that adopts newer skills and technologies, your ability to innovate increases. Then those innovations generate even more skills and technologies. The wheel keeps turning. And advancements keep happening.

When analytics skills and technologies are being applied, we see changes progressing in four steps:

  1. Modernizing with analytics gives you the ability to trust the numbers and rely on a single version of the truth. That’s what Italian credit agency Agos needed when it acquired another big lender, and what Wyndham Exchange & Rentals needed for its vacation ownership exchange, where the ability to create models based on information you already have is crucial.
  2. Integration of analytics into business processes can help spread analytics throughout the organization. The democratization of analytics happens through data visualization and automation. For example, Taipei Medical University uses visual analytics to dig deeper into daily revenue and expense trends. Visualization is widely considered to be a top technique for gaining the most value from big data. To close the gap between analytics and business users, visualize the data. Professor Bart Baesens explains more.
  3. Innovation, as we discussed above, is both a product and an enabler of technology. An important function of technology is that it gives us the ability to do things that previously were not possible. I have seen many mature analytics implementations in the telecom industry over the last few months. Processing speeds have gone from hours to seconds, while total cost of ownership has been reduced by millions of dollars. One CEO told me his company’s earnings increased 30 percent as a result of running 1,000 micro-campaigns created from 5,000 models daily! He promised to share his story with us in an upcoming issue.
  4. Transformation takes place when organizations have mastered modernization, integration and innovation. Businesses in this phase have reached a point where both integration and innovation occur in tandem. Two decades ago, online advertising was just an idea. Today, it is a fast-growing, rapidly developing industry thanks to the ability technology has given us to turn data into insight and new revenue streams through software as a service.

How can you modernize your organization? Consider how to leverage newer technologies like grid, high-performance analytics and Hadoop. Delve into your existing processes and see where analytics can be integrated seamlessly to increase value in your organization. Consider how you can use analytics to innovate in your industry with new products and services. Finally, use analytics to transform your company to create a new market that never existed before.

The time to modernize is now. Those who don’t risk being left behind in our increasingly dynamic and interconnected world. As you will see in the following pages, our challenges are growing more complex, but the potential for data to provide knowledge and insight to tackle these challenges is growing just as quickly – if not faster.

Unlike other technology-driven innovations, modernization does not start with growing your IT budgets. Most of our successful customers report substantial total cost savings from the very beginning. Modernization is about smaller, smarter, more strategic engagements that yield immediate value and provide a path to accelerate innovation.

With analytics entering a new, more powerful era, modernization is now at the forefront. Exploit the countless, value-laden opportunities for accelerating innovation using big data analytics. Consider how you can help your organization improve performance, transform your business and turn big data into big dollars. At the same time, you’ll create a better experience for customers and clients and a great place to work for your employees, one that stands out in every way.

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4 tips for modern CIOs

My first tip is a bonus: If you’re going to participate in a corporate Webcast series, find someone as honest and engaging as James Dallas to film it with you. Dallas, the former CIO of Medtronic, is not only interesting. He also knows a thing or two about implementing advanced analytics projects.

In a series of four brief webcasts, Dallas and I discuss the value of analytics, and how to overcome four myths surrounding IT’s role with data and analytics projects.  Those myths are:

  • Myth 1: IT controls all data.
  • Myth 2: Technology poses the biggest challenge.
  • Myth 3: Everyone understands the value of analytics.
  • Myth 4: You can’t have analytics without IT.

The advice in the webcasts is wide ranging, so I've pulled together 4 tips here to give you a taste of the topics you’ll hear us discuss during the webcast:

For Myth #1: Embrace the messiness. Data is messy by its very nature. The enterprise data warehouse put structure around a lot of messy data, but now, along comes Hadoop without any structure at all: You just flatten your data out and dump it all in. The cultural change is letting go of the structure and accepting that part of this is going to be messy. Anybody who wants to innovate has to deal with messiness, blind alleys and failures.

For Myth #2: Think of Hadoop as an enabler. Too many IT shops are viewing Hadoop as another data warehousing option at a lower cost. As a result, every Hadoop vendor is putting a SQL front end on Hadoop. Why? Just so we can have another EDW at a lower cost? If you’re just treating it as a cheaper EDW, you’re missing the point. Hadoop data structures look very similar to SAS data sets, so they are already optimized for analytics. With the right combination of Hadoop and SAS, you’re making an investment in big analytics to answer questions faster.

For Myth #3: Ask better questions. As an industry many of the developers we hire in IT come from  Computer Science programs that train students mostly about systems like databases, workflow engines, and web servers.  A great programmer is likely to approach a business process problem like Einstein did, as a thought experiment. An example is asking a programmer to optimize a supply chain. They can write a simulation using lifo and fifo queues but may not know the opportunity to apply optimization algorithms.  It wasn’t until later in his career that Einstein realized the value of math and analytics in helping him answer some of the most vexing questions. IT should have those same skills. We need to train IT staff about the basics of machine learning, forecasting, and optimization if we want to help the business answer their most vexing questions about customer churn, portfolio risk or supply chain logistics.

For Myth #4: Balance the portfolio of what you do as CIO. Are you spending as much energy getting information out to users as you are getting information in? Companies invest millions in ERP systems, business payroll software and healthcare benefits technologies – to name a few. Are you balancing the work that goes into those systems with the data that can come out of them? What none of these systems solve is what SAS has solved all along: How do you get all that data, bring it back together and analyze it to get answers?

I encourage you to watch the analytics myths webcast series for more. Each segment is 10-15 minutes, and they also include clips of interviews with IT leaders in various industries.

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Developing tomorrow’s analytic talent

I speak with executives in every industry – in companies big and small – and they all have the same challenge: They’re overwhelmed with data. The problem? There’s a huge gap between the amount of data they possess and the number of employees who can analyze it. This lack of people power is causing companies to miss out on critical opportunities that are hidden in all that data.

Easy fix, right? Just hire more data experts. But those same executives tell me they have a hard time finding and retaining that valuable talent. My answer is, look to our universities.

Hire more college graduates

Do you hire for experience or potential? There are arguments for both, but I see future dividends in developing the analytical minds of the millennial generation. This effort must begin well before graduation day, and I’m excited to be part of the SAS team taking action to tackle this problem. We’re creating a talent pool to fill these jobs – and that will help SAS customers and partners succeed.

I recently attended Analytics Day at Oklahoma State University, an event I’ve attended for several years. Generating interest in technology careers is always my goal. It’s something I’m passionate about – I want every student to have the opportunity to become an analytics expert.

That’s a goal shared by all of us at SAS, and we’ve been working toward it for a long time. More than seven years ago, SAS and North Carolina State University launched the first analytics master’s degree. That was before the demand for graduates with big data skills increased dramatically. With such an upturn in the demand, we will expand our outreach.

SAS® Analytics U helps anyone become an expert

Our latest initiative to attract more talent is SAS Analytics U. SAS Analytics U is open to professors, students and academic researchers. Access to free SAS software paves the way for anyone to become an analytic expert. And a vibrant online community encourages collaboration with other SAS users. All of this support helps develop the deep analytical talent that companies are looking for.

Online courses also serve as an important instrument in creating more talent. SAS’ upcoming online and massive open online courses (MOOCs) will be open to anyone who wants to learn SAS programming, prepare for certification, increase marketability and enhance skills.

Analytics boot camp

The best and the brightest hate to be bored, so when SAS hires college graduates we put them through a rigorous, 12-week Technology Enablement Academy designed to immerse participants in core SAS technologies. Together with seasoned mentors, they immediately build a network based on relationships with two-way communication. The knowledge sharing benefits customers, employees and SAS. These new hires are quickly assigned to customer projects, solving challenges and testing the limits of their knowledge. We’ve seen these graduates have an immediate impact. They’re valued team members, not just the new kids on the block.

Between SAS Analytics U, our online courses and academic communities, we’re doing everything we can to help students get real-world technology and analytics experience. So get ready – soon you’ll be meeting the next generation of analytics leaders.

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