As 2014 slowly winds down it’s time to gear up for the holiday shopping rush. As in recent years the Consumer Electronics Association reports tech gifts will again be high on everyone’s list this holiday shopping season. A new addition to the list this year are numerous Internet of Things (IoT) must-have gizmos.
The wifkettle is the perfect gift for those who can’t bear the idea of getting out of bed without a cup of hot tea awaiting them. The iKettle is a Wi-Fi-enabled device that communicates with your iPhone or Android device. You control when the kettle starts boiling and can set the temperature you want the water to be when finished.
2014 holiday shopping research results (click to enlarge)
‘Tis the day before T-Day and all through the mall
The shoppers are waiting for prices to fall.
The signs they are printed and ready to hang
In hopes that “Black Thursday” will start with a bang.
The family has traveled and all gathered here
To spend time with grandma and bring her good cheer.
The meal has been planned and the table’s been laid,
The turkey’s defrosting and the pie’s being made.
And mom in her yoga pants and I in my tee
Have just settled down to watch some TV.
When believe it or not the commercials were clear
Most retailers will open for shopping this year.
Starting tomorrow (not Friday) they say
The discounts are better on Thanksgiving Day.
No post turkey nap; what’s more, no football.
The plans have now changed, we must go to the mall.
Having worked in analytics for over 25 years, I’ve never really felt part of the ‘cool gang’. However that’s changing and all of a sudden, at long last, it is "chic to be geek!"
Research published by SAS UK and the Tech Partnership reveals that from 2013 to 2020, the big data workforce in the United Kingdom is expected to grow by around 346,000, pushing the rate of job growth in big data up to 160 percent.
There'll be around 56,000 job opportunities a year in 2020 for big data professionals. However, our research also shows that there are already serious skills shortages in jobs requiring big data skills, with recruitment companies reporting that three quarters (77 precent) of positions were either "very" or "fairly" difficult to fill. The spread of big data roles advertised shows that between 2012 and 2013, 96 percent of all advertised big data positions were in England and that six in 10 (63 percent) were based in London. Read More »
For many industries, big data analytics have opened numerous doors for more employees to be groundbreaking and to challenge the corporate status quo.
Prior to big data technologies, risk taking behaviors were primarily reserved for provocative souls who stretched organizational boundaries to disrupt industries, such as airline revenue management.
There were winners and losers but many of these trailblazers are recognized today as industry revolutionaries leaving a path of change behind them. With big data analytics various personas can become their own industry trailblazer.
So what exactly does this mean? At the inaugural Broadcast IT Society meeting in NYC hosted by the Media and Entertainment Services Alliance (MESA) major television broadcasting executives from the likes of NBCUniversal, CBS, Viacom, HBO, AMC Networks, Turner, A&E Networks, WNET, plus SAS’ own Dan Hawks, Principal Media Industry Consultant discused the changing role of IT in today’s digital broadcast world. The IT discussion encompassed digital/big data, cloud, consumer centric models, connectivity, wireless and more.
Well, this is a kick to the giblets. I assumed when I was summoned to the White House it was in recognition of my tireless advocacy for turkey rights. I wasn’t expecting a press conference in the rose garden or anything, just a meet and greet with the prez and a quick photo. Maybe a White House tour …
I’m getting a tour, alright, but it’s the special coop-to-kitchen tour. I’m this year’s White House Thanksgiving turkey! Hooray! What an honor! What a crock. I should have known my crusade against Thanksgiving would get me in trouble.
It’s too late for me now, but I’m sharing my Thanksgiving data visualization dashboard in hopes that my feathered brethren will take up the mantle and keep fighting the good fight. Not you, wild turkeys. I tried to recruit you but it was all, “Tough luck, Butterball” and “Have you tried my bourbon?” Very funny…your day will come.
As a simulation exercise, SAS has created a fictitious oil portfolio, VirtualOil, which readers can use as a generic benchmark against their physical oil commodity book’s performance. Each month, we reflect on what the visual analytics can tell us about the portfolio’s movement, with additional commentary and granular chart views below.
VirtualOil picked an intriguing time to get into the business. In early November, Saudi moves to cut oil prices for the second month in a row had commodity traders speculating about a price war in an already soft price environment.
Are major exporters trying to nip US domestic oil production in the bud? As the price of oil continues its precipitous slide from three-digit highs to the mid-$70s, some North American fracking operations have become uneconomical. While these unconventional operations have been shuttered as the price dips, VirtualOil’s purely derivatives-based portfolio continues to exercise its option to produce. With a strike price set at $50 all-in, VirtualOil is still in the money and investing returns at 5 percent.
Every day there are news stories of fraud perpetrated against federal government programs. Topping the list are Medicaid and Medicare schemes which costs taxpayers an estimated $100 billion a year. Fraud also is rampant in other important federal programs, including unemployment and disability benefits, health care, food stamps, tax collection, Social Security and the list goes on an on.
Fraudsters have become more sophisticated, and the importance of using technology to empower anti-fraud controls has never been greater. Analytics can be used to identify anomalies and fraud patterns, as well as match and link the malignant social network of well-organized crime networks.
Today’s healthcare system is under tremendous pressure to reduce overall costs without losing track of the patient. Legislative changes and challenging economic realities make it increasingly difficult to deliver both improved outcomes and cost savings for the most complex patients.
The Physicians Pharmacy Alliance (PPA) recognizes the changing healthcare landscape and is working to reduce overall healthcare costs by driving improvements in medication adherence, reducing utilization and delivering patient-centered services. An analytically-driven organization, PPA uses SAS to help control costs, identify risk, engage patients and provide comprehensive reporting of activity and results to all members of the care team.
I recently traveled to a Consumer Packaged Company (CPG) headquarters to discuss ways to improve their inventory positions compared to those of their chief competitors. I got to meet with many of the top managers and analysts involved in their supply chain group, and I came away with a new appreciation for the challenges that CPG companies face in today's marketplace.
This supply chain team seemed to be stuck. They had an inventory optimization system installed, but they had not done a lot of updating due to the time and effort it required to create what-if scenarios. Indeed, many of the original team members had left and the new members were relying on spreadsheets and rule-of-thumb business rules.
I asked the following question: "Why are you trying to attain a service level of 95 percent at your central warehouse in California when your downstream warehouses are also positioned with 98 percent service level?"
Many vendors claim they have analytics, and a lot of users have embraced the belief that analytics is the way to go. But what does analytics really mean, especially to business users without statistics backgrounds, and how much do they need to know about analytics to be able to make sense of the results?
I would like to start with a quick brain game. The two following charts show historic sales across time. Starting on the vertical line, what we see are forecasted sales numbers. Which of the two forecast charts would you think is more accurate or do you feel is more trustworthy?