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The SAS Data Management community
How many times a day do you search (or “Google”) how to do something with a product, the best ways to perform “X,” or for help with a problem? Chances are it’s a lot, and when you do, you likely land on a forum where your peers have posted answers ten times over. This is the beauty of online communities. And I get to see it every day.
As community manager for three of the SAS Support Communities – Data Mining, Data Management and SAS Visual Analytics – I see lively exchanges between SAS customers and employees by the hour. I flag customer quotes that give me warm fuzzies like:
“Excellent article and discussion; I'll certainly be sending it along to many of my colleagues.”
“Thanks for all the resources! Looks like I’ve got plenty of reading ahead of me.”
“I always learn something new when I post in this forum. Just what I needed.”
“I’m so new to this field. Your answer is so helpful.”
“I like the responsiveness and expertise of this forum.”
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Let’s face it. We are living in a new era – not just on the cusp of one – when it comes to personal, professional and connected relationships. This new era is defined by our constant, near real-time connections and the ability to share and receive information instantaneously using a combination of social, mobile, analytics and cloud technologies.
These four technologies are sometimes referred to with the acronym SMAC, which was originally associated with the Gen-Y demographic. After all, this generation pioneered the use of mobility and cloud portal applications to connect, interact and engage in open informational exchanges.
Facebook, Tumblr, Twitter and YouTube, for example, provide public platforms to create and share content that also can be analyzed for trends and insights at the crowd-source level or the individual level. A stunning array of compute power to the people.
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Rom Hendler, Chief Administrative Officer for the Las Vegas Sands
Rom Hendler is a firm believer in managing marketing with analytics. “Creative marketing campaigns are important, but the nuts and bolts of great marketing are driven by analytics and a tight alignment between the chief marketing officer and the chief information officer,” says Hendler.
In his previous job as the vice president of strategic marketing at a major Las Vegas casino, Hendler synced revenue management with marketing data to keep occupancy rates high at the best price the market could bear. He has a particular interest in using analytics to predict what a customer will do next – and adjusting marketing offers to retain loyal customers.
At Las Vegas Sands Corp., he briefly served as both the CMO and interim CIO. “At that time, the partnership between the CMO and the CIO was excellent,” laughed Hendler.
He’s now the chief administrative officer for the Sands, and continues to champion analytics as the lifeblood of any business-to-consumer company. Hendler will share his experience and examples during the Leading Marketing Excellence With Analytics panel at The Premier Leadership Series (PBLS) in Las Vegas on Wednesday, Oct. 22, at 2:15 p.m.
Hendler took a few moments out of his busy schedule to share some of his advice for data-driven marketing:
- Align the CMO and CIO functions. Customer-centricity isn’t possible without a strong partnership between the CMO and CIO.
- Select the best technology. Technology is the driving force behind delivering a consistent customer experience, more so than marketing gurus and brand savants.
- Hire the talent you need. Understanding how to tweak marketing offers and making sure an offer doesn’t end up costing the company money is impossible without high-quality analytics, carefully managed data and the analysts who can uncover those insights. “You need someone who understands the needs of the business and the technology,’’ says Hendler.
“CMO is not the same job it was even just a few years ago,” says Hendler. “It used to be about brand and communication skills. Now CMOs need to have analytical talent.”
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I recently caught up with Dr. Tom Davenport, analytics thought-leader and author of Big Data @ Work, in Dublin, where we talked about big data, the Internet of Things and Hadoop. I'll be sharing the conversation here with you in two parts. You'll find part one below, and you can check back next week for part two.
John Farrelly: I'd like to start by discussing your new book, Big Data @ Work, and how it dispels the myths and outlines the opportunities concerning big data. What have you come across since starting to write the book last year?
Tom Davenport: A year ago, it became apparent that big companies were starting to experiment with big data. They were telling me, "We know that analytics is important, we get that we need big data; but how do we seamlessly integrate big data and our existing small data analytics?" Also, "How do we increase the speed and scale on which we're using this, and how do we move towards incorporating machine-learning in addition to the traditional hypothesis-driven approach?" A lot of organizations have been doing this for some time, but I also spoke to companies such as Allied Irish Bank, Icon, UPS and USAA about their pilot projects.
So, the book is a compilation of how large organizations, who had some small data analytics in place, were achieving this. Jill Dyché from SAS drafted the technology chapter, but I also wanted to look at this from a cultural perspective.
John: Did you come across any particularly good examples?
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Want to know how much the Target and Home Depot cyberattacks cost those companies? According to Forbes, the price tag for data breach expenses ran $146 million for Target and is estimated at $62 million for Home Depot. Even financial institutions, once thought better protected, are reporting massive security breaches, as the recent J.P. Morgan news highlights.
Ray Boisvert, CEO and founder of I-Sec Integrated Strategies
These events have laid bare an ugly truth: Traditional firewalls and anti-virus software can’t thwart hackers bent on infiltrating corporate and government systems for financial or political gain. Ray Boisvert, CEO and founder of I-Sec Integrated Strategies (ISECIS), will address the issue at The Premier Business Leadership Series in Las Vegas, Oct. 21-23.
As the former Assistant Director of Intelligence for the Canadian Security Intelligence Service (CSIS), Boisvert is uniquely qualified to help businesses and governments identify risks and create cybersecurity safeguards. His advice? “A new approach that uses analytics to understand the behavioral aspects of hackers is absolutely necessary,” he says.
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Working out where Hadoop might fit alongside, or where it might replace components, of existing IT architectures is a question on the minds of every organization that is being drawn towards the promises of Hadoop. That is the main focus of this blog along with discussions of some of the reasons they are drawn towards Hadoop.
For the past 12 months, I have spent a great deal of time speaking to organizations that were either thinking about adopting Hadoop as a data platform or were already well underway with their Hadoop journey. During this time, I have heard two core arguments as to why people want to adopt Hadoop: cost and agility. Perhaps unsurprisingly if you talk to those that have implemented, they often tout the same two things as the benefits of having adopted Hadoop. Lets dig into both.
Cheaper in many ways
The most frequent argument I hear is that using Hadoop as a data platform is economically efficient. I am consistently told that the cost of the software and support, per node or CPU, is significantly cheaper than almost every relational database management system (RDBMS) on the market by those who have adopted it. In addition, they tell me that the commodity hardware used by Hadoop is always a lot cheaper than the hardware organizations are advised to use in support of an RDBMS or a specialty appliance. One reason for the cost reduction is that redundancy is built into the system with Hadoop, so you do not need to worry too much about things such as redundant power supplies or disks, as a failed node in Hadoop is not a big deal.
In addition, many Hadoop users cite the fact that you can just upgrade disk and memory on nodes pretty much independently of the software licenses and other formalities as a major benefit. Likewise, I'm told, if an organization wants more CPUs in their Hadoop cluster, to aid with increased processing capability, it would not result in a rather significant and unrequired additional RDBMS license cost so incremental upgrades do not break the IT budget and are pretty predictable.
In adopting Hadoop as a data platform, organizations are hoping to slow down the burgeoning RDBMS growth, which is now starting to be a significant cost for many organizations, or to entertain the idea of taking the RDBMS out of much of the picture as data volumes grow except where it is really needed. Hadoop is seen as the route to cost effectively implement a data platform that is capable of handling the current explosion in data volumes and the continued acceleration of data that is expected with the Internet of Things.
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After attending the SAS Day at Texas A&M University on Oct. 2, I came away with a new perspective on some of the different educational offerings to help fill the analytic talent gap (which according to studies and research continues to grow). In essence, there is a yin and yang of where to find your data scientists. While your company may need to hire new employees, you may also find that you have employees right under your nose who want to grow their careers while benefiting the company at the same time.
Universities from across the world are developing new programs and degrees to help meet this demand on both sides of the equation. While many programs like North Carolina State University's (NC State) Master of Science in Analytics, provide graduate level education in a full-time 10-month program, Texas A&M's program offers a part-time, five semester Master of Science in Analytics open to working professionals.
Programs like NC State’s help develop new data scientists to enter the workforce, while Texas A&M's program is geared toward helping companies develop employees already within their workforce who possess a foundation of skills that can be further developed to fill these data scientist roles. And there you have it – the yin and the yang of where to find your data scientists!
Both types of programs are essential to help companies invest in the analytic talent they need to remain competitive, whether that means hiring new employees or investing in your existing workforce. This is why SAS is actively involved in providing support for programs like these at many universities, as well as providing teachers and students with free access to SAS Analytics via our Analytics U program. With these kinds of investments across the board in analytics education, I am optimistic the skills gap will continue to narrow.
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Today’s self-parking cars are a marvel, but that’s nothing compared to what’s just around the corner: Autonomous vehicles that can taxi you efficiently around a city, onboard navigation systems that warn of bad drivers or traffic jams nearby and offer safer, quicker alternative routes; trucks that haul commerce safely and quickly across the country, avoiding traffic delays and optimizing part replacement needs.
Andreas Mai, Director of Smart Connected Vehicles for Cisco
That’s the Internet of Cars, and it’s what Andreas Mai, Director of Smart Connected Vehicles for Cisco, will be talking about at The Premier Business Leadership Series in Las Vegas, Oct. 21-23.
Mai’s particular passion is the art of the possible and exploring how personal transportation can and will change as the Internet of Things becomes a reality. The implications for individuals, society, government and business are profound. And since Cisco is at the forefront of the connected car movement, Mai has had the opportunity to be in discussions at the highest levels of government and business.
“One concept we’ve discussed is the convergence of personal and public transportation,” says Mai. “The Internet of Cars will bring automakers, government, telecommunications and other companies together to share information and work on optimizing the public infrastructure. They’ll all need to partner to deliver new and better services.
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On Wednesday, October 15, Ed and I will be spending the morning at the North Carolina Museum of Natural Sciences. It’s a great museum, and I always love going there, but that day holds an especially cool event. It’s called the STEM Career Showcase for Students with Disabilities. (If you don’t know what STEM is, it stands for Science, Technology, Engineering, Math).
We have a fun morning planned. We’ll have middle-school and high-school students with disabilities joining us. They’ll hear a group of amazing speakers, watch a game show of college students, and interact with a panel of STEM professionals with disabilities who are there to share how they achieved professional success.
On-site registration is already closed, but you can participate from anywhere in the world. We’ll be livestreaming the entire event. So listen in and feel free to submit questions! You might even see me; I’ll be the gorgeous dog at Ed’s side.
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Depending on whether you are a half-full or a half-empty kind of person, the "big data" revolution is either a tremendous windfall for the career of a statistician, or the makings of a real existential crisis. As with most things, it’s probably a bit of both.
On the one hand, the Harvard Business Review calls data science the sexiest job of the 21st century. Since at least some statisticians would seem very qualified to fill in that role, AND those well-paying jobs, statisticians look ready to cash in on a very rewarding career indeed.
Yet on the other hand, statisticians are taught from the very beginning, FROM THE FIRST FIVE MINUTES OF STATS 101, about the values of a rigorous experimental design, of making sure there is a representative sample, and above all else, to never…ever jump to any premature conclusions. In the "big analytics" age of doing all the analyses on all of the data, statisticians often find this basic premise challenged.