Father’s Day data visualization reveals…do not feed your brother cat food!

As a proud father of three young children, Father’s Day is very special to me. I pulled together some data about the holiday for a fun blog post, but with three kids it’s difficult to find time to write. Evenings end with me and my wife collapsed on the couch debating whether we can maintain consciousness through an hour long DVR’d show, or if we shouId just go with a sitcom.

The kids are happily playing together so, powered by coffee, I’ll try and bang this out. I hope you enjoy some of these tidbits. I particularly find interesting the data on…

[Cam, I appreciate that you can rhyme words with “butt”. You don’t have to repeat them over and over. Daddy’s trying to work here, OK? Thanks.]

So…uhhh…the data. Right. Using SAS Visual Analytics, it was easy to visualize data on gifts, spending and other aspects of Father’s Day in a variety of ways.

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Data scientist career advice from dear old dad

As we approach Father's Day 2015, I recall that many years ago when I was in high school and college my dad had lots of ideas about what I should do with my life. Many of these career ideas were influenced by whatever recent magazine article he had read. Among his suggestions were oceanographer, Japanese translator and dermatologist. I don’t think I gave one of them more than a half second of thought.

But SAS Student Ambassador Catherine LaChapelle, recently graduated from the University of North Carolina, has more sense than me. Or at least her dad, a SAS R&D team member, had better suggestions than mine.

In this video, recorded earlier this year at SAS Global Forum, Catherine explains how she has taken her dad Carl’s suggestions about a career in data science and her own interest in politics to create a mashup career plan. Her undergraduate degree from UNC is in political science and her honors thesis uses SAS software to analyze how public sentiment about crime correlates to actual incarceration rates over the years.

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UK Hadoopists: fashionably late to the big data party

People are such an important aspect of data analytics. I was reminded of this at the recent Strata+Hadoop World event, where I saw first hand that the UK is indeed facing the same skills gaps as elsewhere in the world. Perhaps that didn’t surprise me, but I also noticed the different journey the UK has taken to adopting big data analytics.

Party

Without delving too deeply into the UK's use of big data analytics as compared to other markets, we can see at least one stark difference: that the late adoption of big data has been a help, not a hindrance. While US companies might have vast amounts of data to work through, in general, UK companies are not facing this same scale of project quite as often. Instead, the UK is mainly facing the complexities of incorporating and consolidating a wide variety of distributed data – from a variety of different sources and located in different parts of the business.

Thanks to its late arrival at the party, data analysts in UK businesses can look at the experiences of US companies and learn from how they’ve overcome those challenges of volume and complexity.

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Education leaders need data visualization too

Did you know that the education industry is heavily embracing data visualization to run their business? Just like any other industry, leaders in education need to understand their customers (i.e. students). They need to understand how the students are doing, how they're progressing and if intervention is needed to ensure they're successful. They need to do accountability and compliance reporting to the state and federal government on their students and programs. They also need to ensure that all the resources students need are in place -- facilities, materials, teachers, professors, courses, etc. This list is just a small sample of the types of things they're doing with data.

In my last post, I shared several customer presentations on SAS® Visual Analytics from SAS Global Forum 2015. Looking at those you can see other applications for data visualization. But, it all boils down to having accurate information readily available to make data-informed decisions.

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Self-service BI and approachable analytics for all

Still think business intelligence (BI) and analytics are only for big companies? The truth is, small to medium size enterprises (SMEs) can benefit from BI and analytics in a big way.

Digital disruption

Thanks to innovative new developments SME’s (and small teams who haven't yet gotten IT’s attention) can now use BI and analytics without buying expensive hardware and software, and without hiring expensive technical or analytical skills.

Depending on the size and the vision of the enterprise, they can now choose between various formulas and deployment methods (on premise or in the cloud) in order to start using their data to improve business processes. The bottom line? They can start to experiment with BI and analytics with a minimum investment.

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The pros and cons of innovation labs

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Jill Dyché, VP of SAS Best Practices, talks about innovation at the SAS Global Forum Executive Conference

How is it that some companies can come up with a big idea and implement that idea successfully in the market, while others never get past the idea phase?

"In the case of innovation," says Jill Dyché, VP of SAS Best Practices, "big ideas aren't enough."

It's also not enough to just "put some smart guys together in a room," says Dyché. What is enough? Innovation needs to be purposeful, collaborative and supported by the culture in your organization.

To accomplish innovation, she recommends an innovation lab, a physical space that centralizes big thinking and deployment of innovation, and isolates innovation from the rest of the organization.

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Does OT + analytics = IoT?

42-40999995Operations technology (OT), such as control systems, are crucial elements in our daily lives. They make the stoplights function at intersections. They guide robots with precise movements on the shop floor. Their switches and routers are the backbone of our internet.

But what if they were even more intelligent? What if the actions of OT were guided not only by engineering principles but by data, prescriptive instruction based on advanced analysis and informed by real-time, relevant information? Then, OT systems become responsive to the current conditions of their environment and can even become adaptive.

This is the promise of the Internet of Things: powering OT with analytics.

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Big data use cases and the big data wake up call

168799489According to recent studies on big data readiness, the majority of companies (more than 60 percent in the latest study of Crisp Research) are not prepared for the challenges of digital transformation. In fact, 58 percent of decision makers surveyed say they have no strategy in place.

The quest for the golden use case

Aside from industries and companies that are forced to invest in big data due to their business model (telecommunication and retail, for example), the first steps for the majority of companies in the DACH region are still very hesitant. Most companies are in a process that I like to call "searching for the golden use case," meaning they think they understand the importance of big data so they start searching for the groundbreaking business case. This case has to prove in a short timeframe that big data is worth the investment. Very often, the result is: nothing.

Faced with unimpressive results, early adopters are asking, are the claims about the huge benefits of big data just more hype, or are we doing something wrong? Where are the big data use cases? And how can we do the same?

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Let's talk about things – in the Internet of Things

The Internet has been around a long time. "Things" have been around even longer. Put the things on the Internet, aka the Internet of Things (IoT), and you get so much hype that IoT is at the top of Gartner's "Peak of Inflated Expectations" – and poised for a fall into the "Trough of Disillusionment."

Streaming analytics in IoT

Events stream from sensors or from the outside of things with computer vision. Streaming analytics can distill data for traditional data analytics or act directly. All analytics can originate signals for controllers that actuate things. Streaming analytic models can be refined by big data analytics immediately for improved real-time in-motion analysis.

In spite of the predicted hype deflation, the things have a lot to offer the Internet and not just notions of more big data, faster. Streaming data is part of the nature of things, and event stream processing can help by analyzing those streams in-motion.

To understand why streaming analytics is so important to IoT, you have to look past the "billions and trillions" talk, and look at the architectural fundamentals of IoT. Things stretch the Internet and stress IT infrastructure because their nature is new and different. Consider these characteristics of the things in the Internet of Things:

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Helping retailers get their unfair share

USA Today recently published an article titled 10 retailers take two-thirds of your money. The story highlights the revenue distribution among the Top 100 retailers in the S&P 1500. It was startling to see that such a small number of retail powerhouses take in such a large percentage of consumers’ income. It’s no surprise that Walmart tops the list, and it was interesting to see that CVS, Costco, Kroger and Amazon rounded out the Top 5 spots on the list respectively.

But what do statistics like these mean to retailers not on the USA Today list? For one, the statistics indicate that smaller retailers have less room for error. It says that to remain competitive they must be even more diligent than the Top 10 about how they run their business to capture their fair share . . . and maybe even an unfair share. Read More »

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