Friday, October 30, 2015

Data Scientist Plots Epic Trick-Or-Treat Route For His Son

The sweetest way you can use Big Data? Optimize your trick-or-treat route!

Data Scientist, Zeeshan-ul-hassan Usmani did just this.

Last year, he had his son collect some data on his candy stockpile. He also did some research on his own. With a compilation of the data, they found some pretty interesting things. And this year, his stockpile will be bigger than ever and will contain less (gross) candy corn and more KitKats.

using predictive analytics, you can get less candy corn while trick or treating this Halloween

What does the route look like? Well, it’s a lot different from last year’s route! They found roughly a quarter of the houses last year did not give out candy. Those houses will be skipped this year (they must use the night efficiently).

How can you guarantee a house will give out candy? If the wife is between 41 and 50, and the husband is between 51 and 60, there is a 100% chance you will get candy.

Usmani was even able to tell his son which houses he should visit to get his favorite candy bars. Although Lollipops are the most common candy that is given out, this year, his son will get far more KitKat bars.

using data analysis, you can find ho to get the most KitKat bars this Halloween

He should also visit the homes of “new kids on the block.” Clearly the newcomers are trying to earn brownie points…or should we say candy points?

The amount of data, knowledge and information Usmani gathered is borderline creepy…but hey! It’s Halloween!

Big Data Podcast Conversation With A Big Data Detective

Fear of Big Data? Let the data detective talk about Big Data

http://datatalkshow.com/wp-content/uploads/2015/10/data-detective-data-fear-10_30_15-2.48-PM1.m4aworries and why you shouldn’t be worried!

What Do Big Data And Aliens Have In Common?

Big Data and Aliens have little in common other than IBM, NASA and SETI’s interest in them.

IBM has announced that they will be lending their Big Data analytics systems to SETI ( Search for Extra-Terrestrial Intelligence) Institute to aid in their hunt for extra terrestrial life. NASA is also working with IBM and SETI, providing deep space radio signals that may contain signals that lead to a discovery of other life forms.

How can IBM help SETI look for aliens? 

SETI will be utilizing IBM’s Spark system for it’s machine learning qualities. Spark is an open source data system that is continually improving, making it a wonderfully useful tool in searching for the unknown. The deep space radio signals can be processed by Spark to potentially catch any signals that human analysts may have missed.

SETI is extremely excited about the partnership with IBM as their resources have vastly improved. SETI can now search for extra terrestrial life faster and more meticulously. Instead of relying on stargazers and fanatics, SETI now has the help of NASA which means they will receive data on the far out places of space they never had access to before.

This unique partnership is an innovative way to use Big Data. Many companies today are engaging in Big Data Anlalytics to extract information to better their business, but this is the first we are hearing of Big Data working with SETI. Big Data is such a dynamic tool that can be used in almost any realm. From healthcare to banking Big Data is helping people make decisions and discover more accurate information. With IBM, NASA and SETI working together we are making major leaps in the search for intelligence beyond our world.

Just like its effect on other industries, the use of a Big Data analytics system like Spark saves time and money. SETI is now discovering evidence they have been searching for for years! SETI is especially lucky to have their partnership with IBM so that they do not need to run their own Spark system and can simply use IBM’s.

Who knows, maybe in the next ten years we will be tracking extra terrestrial signals in real time, becoming faster and smarter on our hunt to find life forms beyond ourselves.

To learn about how Big Data is being used in other unusual ways check out this interesting article! 

Big Data Podcast Discusses Fear Of Big Data – With A Big Data Detective

Many firms have a fear of Big Data. Why? Let the data detective dispel those fears.

Thursday, October 29, 2015

Cliintel Big Data Company Helps Habitat For Humanity

“Alone we can do so little; together we can do so much.”

~Helen Keller

HFHT_Logo

Focusing on great results and putting others ahead of ourselves are defining values of how our company operates.  There is nothing more important than a good, safe, secure home.  When people have safe housing, they are free to secure a brighter economic future for themselves and their families.

I hope that our commitment to volunteering demonstrates our heartfelt desire to create a better world.

I am always proud of our company, however when I see us spend time giving back to those that are less fortunate, I realize how lucky I am to be part of such a thoughtful and caring organization.

What Is Big Data Really?

We know that Big Data is information, but what kind of information? Is it simple, clearly put information, or a bunch of scattered information? Big Data is a big concept and deserves a more clearly defined explanation.

What is Big Data?

In it’s most organic form- nothing

Raw data is noting, it is a rock that would mean nothing to you unless you had the tools to open it up and harvest the most valuable section of the gemstone. What tools would allow you to extract the meaning from large quantities of data?

Algorithms and Analytics.

According to the Merriam-Webster Dictionary an algorithm is, ” a step-by-step procedure for solving a problem or accomplishing some end especially by a computer”. There are many different types of algorithms that are used to solve different data sets. As no data set is the same, an algorithm must adapt to service the needs of that unique group of data.

So if algorithms are the step by step procedures that allow us to mine through data, where do analytics come in? Analytics are what allow us to draw meaning from the data. If algorithms are what transform raw data into usable data, analytics is how we study the data to draw out the useful information needed to make more educated decisions.

Raw data, algorithms and analytics are a trinity. They all need one another to form results. This isn’t to say that they don’t need other outside sources such as human intuition, but they are the three essential tools when mining data. These tools are what can turn Big Data into Smart Data.

Anyone can collect large amounts of data, but knowing how to turn it into something valuable is the tricky part. You could have terabytes of raw data, but who is to say any of it is good data? By running raw data through algorithms and analytics we can pull out the informational data and weed out the useless data. This is Smart Data, the data that is valuable, that shows the patterns needed to understand a large amount of information and discover insights from them.

When we hear about Big Data in the news, they are really talking about raw data, algorithms and analytics. The goal of Big Data is to unlock Smart Data. With Smart Data we can transform the way the world works, we can see connections never seen before and better our lives because of them.

Let us know what you think about Big Data and Smart Data. Leave us your feedback on our Facebook Page!

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Wednesday, October 28, 2015

The Scary Amount Spent On Halloween

Ever wonder how much Americans actually end up spending on Halloween?

Are you sure you want to know?

It is pretty terrifying…

$7.4 Billion

(Dun Dun Duuuuuh!)

How do you know that? You may ask, well this is where Big Data comes in. The National Retail Federation conducts a survey each year to learn about consumer habits surrounds Halloween. This survey provides the NRF with the data they need to determine spending patterns.

This sort of collected data is what informs stores on which brands of candy to stock up on and how much they should expect to make. Many stores rely on the holiday season to make the majority of their yearly revenue, which is why it is important to study the habits of consumers. Stores want to make as many sales as possible which is why it is crucial for stores to know what their customers want in regards to candy, costumes and decorations.

To understand just how much money these stores are making, lets talk more horrifying data about American spending.

Each Halloween Americans spend,

  • $2.8 Billion on costumes. More money is spent on adult costumes than for kids!
  • $350 Million on pet costumes…. yes costumes for your furry friend.
  • $2 Billion on decorations…. I hope people are reusing them the next year!
  • $2.2 Billion on candy. Dentists will be getting a flood of new clients soon!

Although these numbers are astounding, Halloween is an American tradition that 68.5% of our nation celebrates. It is a spooky time of year where people get to be someone or something other than themselves. Kids learn how to share precious possessions such as candy and adults get to excite in some scares.

See how else Big Data is helping the retail industry learn about consumers and better service their needs. 

If You’re New To Big Data You May Be Wondering What Predictive Analytics Are

Predictive analytics is the prerequisite for generating insight from data.

Simply put, predictive analytics is what allows us to extract value from raw data. It does not matter what size the data set is. It is a type of advanced analytics that allows us to make predictions.

You always hear that Big Data is the new competitive advantage and the new oil. Well, this isn’t exactly true. Because raw data is just that…raw data. It’s when the data is analyzed that it becomes so valuable. By analyzing the data, you can discover inefficiencies, learn more about your customers, and even help break down the barriers of silos.

I now knew how my father felt when I tried to explain the first iPhone to him.

Me: “It is a phone, and an iPod, with a touch-screen, and it has these things called apps.”

Dad: “So do I have to hold my ear up to it to listen to music?”

Me: “No, Dad, you just plug headphones in it, like a normal iPod.”

Dad: “Oh no, I just touched something, and I don’t know where it took me. What button do I press to go back…wait there’s only one button? So what do I do with this?”

The original iPhone, valued at $499, was worthless to my Dad. He couldn’t use the thing.

It is the exact same situation with data. Although it is clearly valuable, it is essentially worthless unless you know how to use it.

Therefore, I see it as predictive analytics is what adds value to data. It is also what can help you make money using data.

Data Podcast: What Is a Data Scientist?

play-309042_1280


http://www.stitcher.com/podcast/data-talk-show/e/40956102?autoplay=true

OSAKA WINS WTA RISING STARS!!!

ProWorld’s Naomi Osaka is the first champion at the BNP Paribas WTA Finals Singapore presented by SC Global, ousting Caroline Garcia in the WTA Rising Stars Invitational final.

Many of you knew her as the talented up-and-comer who stunned Sam Stosur in the first round of the Bank Of The West Classic in Stanford last summer, but there’s another reason to keep an eye on Japan’s Naomi Osaka now – she’s this year’s WTA Rising Stars Invitational champion.

Osaka, who just turned 18 years old a week ago, held her nerve through a very tense finish to the second set to stun heavy favorite Caroline Garcia in the final on Sunday afternoon, 3-5, 5-4(6), 4-1.

The No.35-ranked Garcia is the second-highest-ranked player Osaka has beaten in her blossoming career after the aforementioned win over Stosur – the Australian was ranked No.19 at the time.

Full Article Here: http://www.wtatennis.com/news/article/5094019/title/osaka-wins-wta-rising-stars-invitational

Using Big Data To Ensure Repeat Sales

I was at the grocery store last night trying to find something for dinner that I didn’t have to cook. I have recently been on a gluten free diet, but was craving pizza, so when I found a delicious looking gluten free pizza I was stoked! As I checked out, the coupon that rolled out with my receipt was for the same type of pizza. I looked at my husband, excitedly explaining that the coupon we had just received was the first coupon I have gotten that I would actually use! Normally the machine prints me out a coupon for something like baby food, which we won’t be needing for a while!

Needless to say, I was impressed that the machine picked up on the fact that if I was buying gluten free pizza now, I will more than likely want to buy another gluten free pizza in the near future.

This is how marketers use Big Data. 

Big Data is used by marketers to learn more about the customers. The more a marketer knows about their targeted demographic, the better they can adapt the product or the customer base to make changes and create repeat sales. If a marketing professional can track a customer’s search habits online for say, shoes- then they can advertise a discount for those very shoes. When this happens to us customers we think, ” wow, this is great, I really wanted those shoes and now they are on sale. This must be a sign, I should get them.” We think it is our lucky day when really it is a strategic play by marketers to gain favor with customers.

If a company can successfully fine tune their targeted demographic based on learning about the wants and needs of their customers, they can ensure repeat sales. People want that one store they know they can rely on to always find what they are looking for. Depending on how well you know your customer’s habits, you can become that store.

To learn more about how Big Data is being used in the Marketing World check out this great read on Big Data and Market Research!

Tuesday, October 27, 2015

Google reportedly won’t take a cut from Android Pay transactions

Payments Industry Research Consulting Double Diamond Group Merchant Aggregation Mobile Payment Facilitator Consultant
Google reportedly won’t take a cut from Android Pay transactions

Android Pay is a near identical clone of Apple Pay, but it won’t be anywhere near as lucrative, according to a new report. Unlike Apple, Google isn’t taking a cut from Android Pay transactions, so the service will literally be offered for free.

The Wall Street Journal reports that the reason for this is “because Visa Inc. and MasterCard Inc., which operate the dominant payment networks, recently standardized their “tokenization” card-security service and made it free, preventing payments services from charging fees to issuers.”

Tokenization is the system that swaps credit card data like account numbers, expiry dates, and security codes with a unique string of numbers (token) that can only be used once. It’s much safer than traditional transactions, because it means credit card details are never shared with merchants.

TechnoBuffalo, June 7, 2015
READ FULL ARTICLE

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MCX Finally Gets Its Interchange Break—After Chase Hands It To Them

When JPMorgan Chase on Monday (Oct. 26) promised new mobile capabilities for its online Chase Pay program next summer, it chose to take a decidedly retailer-oriented approach. With the lures of lower interchange fees plus all of the fraud cost protections of the EMV liability shift without having to accept EMV, Chase has given retailers concrete reasons to push Chase Pay over other payment methods.

The Chase announcement named MCX (and specifically members Walmart, Target, Best Buy and Shell) as premier partner. Interestingly, the interchange reduction effort that caused MCX to form years ago but had been all but abandoned by the group recently is the centerpiece of Chase’s 2016 plans. What MCX couldn’t get on their own was handed to them by Chase.

Chase’s interchange approach for any transactions where the Chase Pay mobile app is used includes “$0 Network Fees, $0 Merchant Processing Fees and $0 Merchant Fraud Liability” along with “fixed pricing” that Chase would be lower than existing interchange rates. Like all interchange fees, the amounts and the discounts will vary from retailer to retailer, based on negotiated deals.

“To generate merchant interest,” Chase will be “offering a fixed price for the duration of the contract. One price for credit and one price for debit,” said Jennifer Roberts, Chase’s president of strategic alliances and loyalty solutions. “We want to have predictability.” In general, though, how much lower are the fees? “It’s safe to say that the merchants are very happy with the deals we have arranged with them. They will give preference to the Chase Pay form of payment.”

That’s the point and it’s the key strategic difference between Chase’s new approach with MCX and Apple’s approach to Apple Pay. Apple Pay is pushing a shopper-oriented approach, where shoppers are being encouraged to use Apple Pay and where the movement to Apple Pay is fueled by consumers pressuring their retailers to accept it. Apple Pay is also focused on the experience and even Chase concedes that Apple Pay’s NFC transactions are generally going to be faster and easier than Chase Pay, although not by much.

But to deliver that experience and speed boost, Apple Pay requires merchants to have NFC readers. That is preventing the overwhelming majority of merchants from accepting Apple Pay, even if it wanted to.

Step in Chase. Chase Pay is slated to use quite a few different payment technologies—including QR codes, beacons, GPS geolocation and taking a picture of a restaurant check—but not NFC. That allows Chase’s payment method to work at almost any merchant. By giving the merchants a financial incentive to push Chase Pay over other forms of payment, Chase is reversing the Apple model. Instead of getting consumers to encourage merchants, Chase is getting merchants to influence its consumers.

Roberts argued that retailers can use in-store signage and might position Chase Pay as the first form of payment available in that retailer’s own mobile app. That said, Chase’s app is limited to Chase customers, whereas Apple Pay accepts cards from a wide range of financial institutions. And even though Chase touts “its 94 million credit, debit and pre-paid card accounts,” many of those customers won’t use Chase Pay and there are far more consumers who do not have a Chase card than those who do. Therefore, Chase Pay is, at best, a supplemental payment option. MCX wants it to supplement its own CurrentC mobile wallet, of course.

In another key approach difference from Apple Pay—and, for that matter, from every other major mobile payment method attempted—is that Chase isn’t going with any one payment technology method. On the down side, using so many different approaches could slow down acceptance as it is forcing shoppers to get comfortable with multiple mobile payment approaches. This learned behavior will simply take longer.

But Chase is opting for a vertical approach, on the rationale that the best payment method—for both the retailer and the consumer—is going to be different for someone in a drive-through window versus paying at a gas station pump versus paying a dinner check at a sit-down restaurant. “We opted for one solution per merchant vertical,” Roberts said. “We have one solution for fuel that will work across all different” gas stations.

For in-store retail transactions, the mobile device scanning—or displaying—a QR code will be the route. Beacons will be favored for drive-through and for quick-service restaurants (QSRs) in general. GPS authentication will be an option at gas stations, Roberts said. “The fuel re-terminilizations for EMV are very costly at the pump. We’ll be using GPS with the customer having to enter a code into the pump.” At sit-down restaurants, where a commonly-cited pain point is waiting at the table for a server to process the check, allowing the consumer to take a picture of the bill and pay with a mobile device could work well. (Note: When Chase figures out a way to get the server to bring the check right away, we’ll be happier.)

EMV plays into this Chase move in two ways. Despite the passing of the October 1 liability shift, most retailers do not yet accept EMV. The idea had been that most of the upgraded EMV-friendly readers would also accept NFC. Hence, the slowdown of EMV acceptance has also slowed down the number of NFC-accepting merchants. That makes Chase’s non-NFC approach even more effective.

But the liability shift protection has been the key carrot used to incent merchants to upgrade to EMV. By offering those fraud protections for retailers not accepting EMV—as long as Chase Pay is used—Chase is potentially further slowing down adoption. Although not a strategic goal, Chase seems willing to let this happen.

“We started with the merchant side of the 2-sided market. Reterminalizing a fuel retailer is very very expensive,” said Chase spokesperson Trish Wexler. “Some merchants are seeing this as a way to leapfrog reterminalizing with EMV. Where do you start balancing out the economics?”

Chase is also pushing integrated mobile loyalty programs and full tokenization. Apple Pay already offers full payment card tokenization and has talked—albeit vaguely—about offering integrated mobile loyalty.

Payments consultant Deana Rich said she saw the liability shift efforts from Chase as having the most potential. “Chase is guaranteeing the merchant against consumer fraud, which means the EMV liability shift reverts back to the ‘way it used to be’ for merchants,” she said. “By next summer, we will better understand the pain borne by the merchant. If that liability switch pain is big, that will greatly affect the appeal of this product.”

Monday, October 26, 2015

Open Data is Transforming How We Think of the Big Apple

A data scientist’s blog is revealing some statistics about New York City that are making people question how great “The City so Nice, They Named it Twice,” really is.

There was a time when data creation, and access to data was limited. Today, this is not the case. Thanks to the easy creation of data, and platforms used to disperse data, we are gaining insights about…well just about everything. Open data provides citizens with information that sometimes makes them skeptical about the cities that they live in and the rules and regulations they are expected to abide by.

Half of Manhattan is within four blocks of a Starbucks. IHOP, in NYC receives a lower restaurant inspection score than White Castle. Rent Stabilized housing is quickly disappearing, making it more difficult for the average “Joe” to live there. While the data shared in these particular posts may raise eyebrows, other posts may make you cringe. These posts typically reveal information that make people question the city’s policies, and even the representatives themselves.

data is showing us the cleanest places to eat in the city and more

Naturally, one of the posts that sparked resident’s animosity for city policies discussed parking tickets. Using open data, the blog’s author and other Big Apple residents discovered something astounding: two fire hydrants in the city were racking in $55,000 annually. Yes, these fire hydrants were making more than the average American. Nurses in New York City make roughly $8,000 less, annually than these two fire hydrants. What’s even worse is that the owners of the cars that received the violations, appeared to have parked legally. The fire hydrants were placed (done strategically?) away from the curb and even further away from the street. Some of the drivers may not have even seen the hydrant.

Open data is revealing information about how much revenue two fire hydrants in New York City earn annually
Luckily, this story does not end sadly, and open data saved the day. The open data was widely shared and distributed, thanks to the Internet of Things, and residents took preventative measures. I am also guessing that the fire hydrant’s income has been greatly reduced.
However, this may make many question the intentions of the local government. Some say that the fire hydrants were strategically placed, in order to receive a higher revenue from citations and tickets.
Another blog post caught a “statistical error,” cited from Mayor de Blasio. The blog post, “Funny Math Fact Check: de Blasio vs. Uber,” calls the Mayor out for “faulty math.” Mayor de Blasio claimed that 2,000 new for-hire vehicles are being added to the streets of New York each month. But according to the data, this is impossible. The actual rate of increase? About half of what de Blasio claimed.
To keep things hopeful, the author of the blog, Ben Wellington declares a mission to change some government policies. The skinny data nerd is trying to make open data more accessible and “cool,” so that more people will respond to the insight provided by the data. As more and more people gain insights from open data, there will be more and more pressure to create data-driven policy-making initiatives.

Open Data and Government


“Data really powers everything that we do.” 

~Jeff Weiner, chief executive of LinkedIn

Big Data Could Have Predicted The South Asia Earthquake

Early this morning South Asia was hit with a massive 7.5 earthquake. The quake centered in Afghanistan and rattled neighboring countries including Pakistan and India. There have been 180 people reported dead and hundreds injured by the earthquake. Included in this death toll are twelve young girls who were trampled when trying to evacuate their school.

Could these deaths have been prevented?

What if the people of Afghanistan knew there would be an earthquake coming their way?

Is it possible to predict the wrath of mother nature? 

With the help of Big Data Analytics- Yes these things are possible. 

Innovative companies such as Terra Seismic are revolutionizing the way we look at earthquake data. We have always relied on gathering data after a quake to try to connect patterns and predict the next big occurrence. Terra Seismic has implemented satellite data to predict large earthquakes before they happen, allowing people to prepare themselves.

Terra Seismic is still relatively new and continues to improve the way we foresee these devastating events, but they have already correctly predicted more than a few quakes including the one that hit the Indonesia Island of Sumatra in March earlier this year. I am not sure if the earthquake that rocked South Asia this morning was predicted, but if it was, how might the repercussions be different?

Besides the massive hit the economy takes when faced with the damages of a natural disaster, many people suffer injuries, lose their homes and often times become homeless. If the people of South Asia had been warned about the earthquake that was coming their way, they could have protected themselves better. People could have avoided being near the less developed areas that are home to very unstable structures. Schools could have practiced evacuation drills to prevent the widespread panic that claimed  the lives of those poor twelve girls. Hospitals could have been stocked, staffed and ready.

It is hard to say if we can truly ever be prepared for a natural disaster, but with the developing technology and Big Data available, we have a much better chance at less devastating effects than we ever have before.

Learn how big data is helping track and predict the patterns of other natural disasters in this informative article.  

DBJ

It AIN’T Gonna be easy Why do people think it is easy to do business overseas? Culture, language, customs and laws are different!

It AIN’T gonna be fast The biggest single cultural difference is the perception of “time”

It AIN’T gonna be free Does your office have staff, machines, phones, vendors, and expenses? Why do you think that would be different abroad?

Your skills AIN’T gonna transfer Well, not completely. You may know all about “channel management” in Wisconsin, but Japan does it differently.

You AIN’T gonna enjoy it always Jet lag. Exhaustion. Lack of language. Cramped flights. Endless meetings. Tricky negotiations.

Your money AIN’T gonna guarantee success. Just because you are the buyer, doesn’t mean you will have an easy time buying what you want.

Your law AIN’T gonna win You AIN’T gonna sue If you do, you AIN’T gonna win If you do you AIN’T gonna collect

You AIN’T playing as equals No matter what your project, the strongest relationship will win…even if your product is better

They AIN’T gonna be transparent Americans say what they mean, and mean what they say. There aren’t many other cultures that do that

You AIN’T gonna succeed if you AIN’T knowing what you are doing

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Always dry your curtains on a gentle cycle (tumble dry is best) with low or no heat.

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Welcome To Your New Home For Payment Facilitator News You Can Use

Welcome to PaymentFacilitator.com, your home for an independent and analytical take on the payments issues of concern for the PF community. For our take on the major changes impacting payment facilitators and why this editorial community is needed right now, please drop by our About Us page.

It seems, though, this Letter From The Editor is best used to not promise what we’ll deliver in the near future, but to tell you what we are delivering to you right now and why those pieces have the information that you’re simply not going to find elsewhere today, especially from the various payments media. Our mission is to deliver stories that challenge your thinking and understanding, pieces that literally surprise you. (If that sounds familiar, some of our team comes from a retail IT media outlet we created several years ago—StorefrontBacktalk, for those in the retail IT space. We’re using the same approach here.)

If you like what you see, please sign up for our free weekly newsletter, to be delivered (as of next week) to your Inbox every Thursday 5 AM East Coast.

State Money Transmitter Rule Slams PFs, ISOs

Written by two patents attorneys who specialize in regulatory issues, this is about a little noticed ruling from Pennsylvania that initially involved charitable contributions. But the case is having the impact of banning all traditional payment processing for nonprofits and religious organizations by any company that is not licensed as a money transmitter. Whether or not this case is replicated by other states—and there’s a very good chance it will be—this is the kind of quiet regulatory ruling that PFs need to understand.

Why Did Most Merchants Miss The EMV Deadline? Many Reasons, But Complexity Is The Top

It’s well known that the EMV October deadline has come and gone, leaving most retailers behind. What is less clear is why and the chief cheerleader for the EMV push candidly discusses what went wrong and how the typical Payment Facilitator is going to have to function, in this no-swipe-land (Ok, a lot of skipes) where the liability shift has happened, but not really.

Financial Futility: Why Chip & PIN Sucks For Small Merchants

Speaking of EMV, there is still a very local segment within payments that is pushing for Chip & PIN, because it is clearly far more secure. (Then again, being more secure than magstripe is like being more bullet-resistant than cotton: It’s not an especially high hurdle.) But whereas Why Did Most Merchants Miss The EMV Deadline? Many Reasons, But Complexity Is The Top talks about the differences between the U.S. markets, Europe and Canada in explaining why Chip & PIN made no sense for the U.S. deployment, Financial Futility: Why Chip & PIN Sucks For Small Merchants talks about how PIN makes no sense at all for retailers below a certain revenue threshold. Indeed, even attempting to push it can further undermine security efforts. And while all of that is going on, mobile payments is offering a highly attractive alternative.

Apple Pay Penetration Stats: The Less We Know, The Better It Is

There has been lots of recent discussion about how far mobile payments have gone and especially Apple Pay’s marketshare. But when examined closely, few of those numbers hold up. Bloomberg, for example, recently quoted an analyst firm saying that one percent of all physical retail sales are done on Apple Pay—a stat that the quoted analyst firm quickly disavowed. We dig into the actual numbers and the PF implications.

The Non-Intuitive World Of Authentication And Social Media

Every day it seems there are a dozen new authentication efforts being announced. But what we found intriguing was a movement using social media data in some non-intuitive ways to authenticate bank and retail customers in physical environments, in realtime. It maintains 10-headshot histories for all social sites, for example, to combat identity thieves who change social photos right before attempting to open a new bank account.

Some Interesting Odds And Ends From Money2020 Announcements

Given that the show just opened, we have chosen a few of the more interesting announcements to give a hint as to where the payments space is today—or at least how they want to be seen, rightly or not.

Do the Holidays Bring us Closer Together?

The hustle and bustle of our everyday lives doesn’t always leave a lot of quality time for the people that we love. With the winter holidays right around the corner – I have begun to wonder, do the holidays really bring us closer together with our loved ones?

Do you find yourself slowing down dramatically and spending more time with your loved ones during the holidays? Is it a time that you commit to reconnecting with your friends, family and loved ones?

Do you see a difference in the way that we communicate with each other during the holiday season? Are we more understanding, nurturing and forgiving? Are you more willing to work on your relationships during this special time of year?

Do the holidays effect your relationships?

Please leave your comments below.

Yoga Master and the Benefits of Yoga – Yoga for Energy Video

Benefits of Yoga

Yoga improves your flexibility, builds muscle strength, protects your spine, boosts your immune system and much more. Practicing yoga makes you happier, helps you focus, improves your balance, increases your self-esteem, builds awareness and many more benefits.

READ MORE

The practice of yoga has many health benefits associated with it, so read below to discover even more benefits of incorporating yoga in to your health and fitness program.

BENEFITS OF YOGA

Yoga Video

8 Minute Yoga For Energy Boost – Vinyasa Flow For Beginners Workout

Yoga Master

“Yoga not just entered my life,” he writes, “but now, it is my life.”

The clear progressive stages of transformation through yoga are documented here. as nowhere else. This new sequence unfolds a practical road-map for knowing and practicing the elevation of the seeker’s awareness – from the physical, to the astral, and to finally to the mental levels -and designates observable milestones to determine one’s progress on the path. It marries the philosophy of Yoga with clear “how-to” instruction…

The Making of a Yoga Master: A Seeker’s Transformation

Integral Yoga

The practice of separate branches of yoga in our lives is known as integral yoga which creates harmony between body, mind, and emotions and stimulates the expression of creativity and the creative potential of people in everyday life.

We strive to make our studio at the Center of Massage Therapy to be a small temple to transmit the principles of integral yoga and making yoga a way of life.

LEARN MORE

CALL 303-777-1151 for Yoga Instruction at the Center of Massage Therapy in Cherry Creek district in Denver, Colorado.

Related Articles:

Origins of Yoga.

What is Yoga Nidra?

Saturday, October 24, 2015

The Beauty of Data Visualization

Data visualization may be the solution to information overload. As humans, we have unique capabilities; we can see patterns and determine connections. But we can only do this if data is presented in a way where we can actually “see” it.

Not all can discover patterns in numbers. We are not all math whizzes. This is why we pay them the big bucks. Not all can discover patterns even in words. I suppose that is why they say repetition is key for presentations- no one will remember it, unless you say it seven times.  But for all the rest of us, data visualization can help us “see” the patterns we would otherwise not.

In many cases, information overload results in there being too much information for us to really draw conclusions. It is easy to analyze a spreadsheet with 10 columns…but not so much if there are 150,000 columns. If this data is represented visually though, we can more easily discover patterns within it.

By using data visualization we gain clarity, and get our answers answered quickly, and relatively easily.

Plus, it is usually pretty cool to look at! And that is why data visualization is a beautiful thing!

Want to learn more about working with data visualization? Want to learn about being a data scientist? Thinking of becoming a data scientist? See how valuable data scientists are Here.

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We can easily see that people eat a lot of chicken. While we could scan a spreadsheet of this data, when it is presented visually, we get a clear understanding, quickly. Plus, it is more fun to look at this visual than a spreadsheet, right?

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Not only does visually data help us draw conclusions more quickly, it also allows us to understand the data better. Seeing is believing. Here we can see how much carbon dioxide New York is emitting. This visual represents carbon dioxide emissions as one-ton spheres.

Watch the video to see why other thought leaders think data visualization is a beautiful thing.

You can watch more videos about data visualization, data management and Big Data on our video site, Big Data Minute.

ATP and WTA Pre-Season Training at ProWorld Tennis in Delray Beach, Florida

Every year before the tennis season starts, ProWorld Tennis prepares its pro athletes with an intense Pre-Season Program.

The program will address technical adjustments and tactical implementations to give our players the strongest start possible.

Confidence is key for a professional athlete. We want our athletes to know and feel that they are mentally and physically ready to endure the demands of a full season.

Join our team and see why so many of the top pros come and train with us to prepare for the long road ahead.

SET THE TONE FOR THE ENTIRE SEASON… Let that sink in for a minute.

JOIN THE TEAM

CALL +1 (561) 706-1601.

Friday, October 23, 2015

Cosmetic Laser Center and Medical Spa – Anniversary Celebration and Sale in Boca Raton – BeautySmart MD

Cosmetic Laser Center and Medical Spa

Come Celebrate BeautySmart, M.D.’s One Year Anniversary in Boca Raton, Florida on Thursday November 12, 2015.

We will have a fashion show, entertainment and 25% OFF Beauty Packages. 5:30-8:30pm.

Catered by Merlino’s Italian restaurant.

BeautySmart, M.D. with Deana Clark, CME and Laura Balda, M.D. Medical Director.

MUST RSVP 561-330-7579

Here at BeautySmart M.D. Medical Spa we take the logical approach to aging smarter and looking younger!

We Offer a Broad Mix of Doctor Supervised Treatments – Affordable for Almost Any Budget.

We are located at:
94 South Federal Highway
Boca Raton, FL 33432

We believe if you feel good on the inside you will look better on the outside, we strive to treat each individual, individually by treating the whole person from the inside out.

We offer many modalities to combine and customize your individual needs.

Specializing in:
Cosmetic Laser Treatments
Laser Hair Removal
Anti-Aging Therapy
Medical Weight Loss
Nutrition Coaching
Body Contouring
Cosmeceuticals
PRP
Micro-Needling
Permanent Makeup
Non-Surgical Facelifts
Cosmetic Fillers
Laser Resurfacing to Reverse Sun Damage, Lines, Wrinkles & Renew Skin Glow & Texture
and more!

CALL 561-330-7579

Cosmetic Laser Center and Medical Spa Skin Care

The Non-Intuitive World Of Authentication And Social Media

A cyberthief walks into a bank branch, fully prepared to impersonate his intended high-net-worth victim. Not only is equipped with fake IDs in the victim’s name, lots of personal information courtesy of social and search engine research, but the thief has even taken the precaution of breaking into his victim’s social accounts and replacing his thief-like face for the victim’s on the victim’s own social sites. If anyone tries to check on the Facebook or LinkedIn site of the victim, the thief’s face would be confirmed.

The banker in this case sits beneath a tiny video camera, one that is aimed at the seat where customers and specifically the facial area. Controls of the banker-facing screen allow the image to be precisely aimed for customers of varying heights. And while the banker is pitching her safe-deposit boxes and other bank services, software does a quick check on the thief’s face. Sure enough, it matches the social media images—but the software notes that those images were all recently changed. The software’s database maintains a record of the last 10 images of everyone it can find—and that history of images foiled our thief’s efforts.

That is the scenario—based on systems in trial with various financial institutions today—spun by a security company called Socure. Their interesting approach is to leverage the vast data of social media—if I say “big data,” please punch me—but to use it authentication in non-traditional ways.

Consider facial recognition and image confirmation in general. In an online application, instead of using a desktop or mobile’s live facial image capture and trying to compare it with Web images of that person, the software does the opposite. It searches for an exact match for that image, on the premise that most thieves will use stock art images and photos they found somewhere on the site. It’s like visiting someone’s LinkedIn site and doing a right-click on that image to use Google Images to search for any instances of that image out there.

Another twist is trying to leverage social-media and geolocation. Scenario: Someone is trying to make a purchase in Argentina, but the software sees that they updated some social sites from New York ten minutes ago. Does that necessitate a fraud alert? The truth is that it depends on which social media site had just been updated.

Why? For a lot of business people, a Twitter or LinkedIn account could be populated by an assistant or colleague. Hence, a geographic difference there would be less of a concern than say Instagram, which is much less likely to be updated by anyone other than the actual user.

And social media is also, well, social. Bogus information or images are likely to generate baffled or suspicious comments from someone’s followers, friends or connections. That’s something else that the Socure software looks for.

“The basis of verifying a customer hasn’t changed much over the years,” said Ken Allen, Socure’s senior VP and the former VP/head of payments at Western Union and senior VP/fraud and debit operations at Capital One. “Banks are slowly starting to evolve on this.”

What is the biggest fraud problem with payments players and banks today? “We need to break apart customer authentication and credit worthiness,” Allen said.

It’s a non-trivial point. The time-honored financial institution focus on credit worthiness is giving identity thieves the distraction they need, one where customer identification/authentication is treated as a footnote. By separating the two important functions, it allows financial players to fight fraudsters much more effectively. (No surprise: Socure solely deals with identification/authentication and offers no credit worthiness services. Plenty of other folk do that.)

It’s frightening that, as Allen pointed out, many of the oldest fraud tactics still work today. This includes criminals using social security numbers associated with minors—so that no one is likely to notice until the victim turns 18—and deceased people. That is because Social Security requires next to zero meaningful authentication before it issues a number, meaning there is little to be verified against later.

It’s not clear how effective social media fueled authentication will prove to be, but for now, it’s better than what most financial institutions are doing.

How Much Do Data Scientists Make?

Big Data is arguably the hottest topic of the year. The people who drive this revolution -Data Scientists. Data scientists mine through mass amounts of data and find the connections that can then be translated into valuable information that would otherwise be very difficult to detect. For those who are smart enough to be a data scientist, it is quite the lucrative business.

So how valuable are Data Scientists? 

The average salary for a data scientists is $118,000 a year. It doesn’t matter if you are a kid straight out of college of a distinguished individual, with a salary like that you are sitting pretty. Now, mining through data isn’t for the faint of heart. Finding meaningful relationships in a mound of data can be like finding a needle in a hay stack and can sometimes take a long time to uncover anything relevant. With that being said, those who have the training and the patience to succeed in this profession have the opportunity to work for some pretty fun companies.

Google has been rated one of the best places to work and they love their data scientists. Google prides themselves on knowing their users and being able to accurately market to individuals, which takes data and a lot of it. According to Glassdoor, Google pays their data scientists anywhere from $137,626 to $149,292 a year. With this type of salary on top of being able to work at one of the most well liked companies, I would say being a Data Scientist at Google would be a pretty great gig.

Facebook is arguably the biggest social media site on the internet today. The amount of data Facebook collects from its users is colossal, which means they rely heavily on Data Scientists. Have you ever wondered why the advertisements surrounding your Facebook page are eerily accurate to your interests and desires. From volleyball gear to engagement rings, Facebook advertisements always had me pinned. This is because the Data Scientists at Facebook take the information they gather from uses and sell it to companies, allowing them to more accurately market to unique demographics. Facebook pays their Data Scientists between $135,098 and $178,789 a year. Again, not too shabby.

IBM is the world’s largest information technology company and its products include hardware, multiple types of software, storage products, and customized microchips. Similar to Big Data itself, IBM has infiltrated almost any industry you can think of. IBM uses the best Data Scientists to partner with these different industries to make change happen and help lead those industries to better efficiency. IBM compensates its Data Scientists with a salary ranging from $108, 984 to $112,984. Sounds like a great position, being paid well, while also getting to work on some of the most innovative and new technology the world has ever seen!

These are just a few of the popular companies that utilize the brains of Data Scientist to make a difference in the world. Data Scientists are slowly improving many of the largest industries from oil and gas to healthcare and these changes will surely effect us all.

Let us know what you think about Data Scientists, are they paid too much, too little, or just right?

Share with us on our Facebook Page! 

Thursday, October 22, 2015

Big Data Video SlideShow – 5 Things A Company Shouldn’t Do With It’s Data

This is a quick and easy Big Data slideshow. Enjoy!

Need Fast Advice On Managing Your Data?

If you need advice on how to manage your data, but don’t have time to watch some long boring lecture- check out this simple slide show! This slide show highlights the key basic principles you must follow when handling data for your company. Check it out, it will take less time for you to learn about how to control your data then it will to make your next cup of coffee!

5 Things You Should Never Do With Your Data!

Let us know what you think

Was this slideshow helpful?

How are you implementing these rules in your company?

Big Data Podcast – What Is A Data Scientist?

So, what really is a data scientist? What do they do and how complicated is the field? Are they really scientists? Listen to this quick Big Data Podcast and see for yourself.

Global Business Advice – The Ten AIN’T’s Of Global Business

Global Business slide show: Top 10 “Ain’ts” of International Business

It AIN’T Gonna be easy Why do people think it is easy to do business overseas? Culture, language, customs and laws are different!

It AIN’T gonna be fast The biggest single cultural difference is the perception of “time”

It AIN’T gonna be free Does your office have staff, machines, phones, vendors, and expenses? Why do you think that would be different abroad?

Your skills AIN’T gonna transfer Well, not completely. You may know all about “channel management” in Wisconsin, but Japan does it differently.

You AIN’T gonna enjoy it always Jet lag. Exhaustion. Lack of language. Cramped flights. Endless meetings. Tricky negotiations.

Your money AIN’T gonna guarantee success. Just because you are the buyer, doesn’t mean you will have an easy time buying what you want.

Your law AIN’T gonna win You AIN’T gonna sue If you do, you AIN’T gonna win If you do you AIN’T gonna collect

You AIN’T playing as equals No matter what your project, the strongest relationship will win…even if your product is better

They AIN’T gonna be transparent Americans say what they mean, and mean what they say. There aren’t many other cultures that do that

You AIN’T gonna succeed if you AIN’T knowing what you are doing

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Global Business Podcast
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What Does a Petabyte Look Like?

We know that all of the words ending in “byte” are measurements of data. They are used to explain how much data a device can store. For some, this is the extent of their knowledge. For many, it is difficult to truly comprehend what exactly those measurements “look like.”

You may be wondering what I mean by “look like.” If I were to ask you, “How big is an inch?” you would likely hold out your index finger and thumb to show me how big an inch is.

But what exactly does a petabyte look like? Because a petabyte is a measurement of data, it isn’t exactly something you could see. So, unlike an inch (a measurement of size), you couldn’t easily show me how much a “byte” of any sort is. But, if you could, what would it look like? How “big” would it be?

It would look like a lineup of 48,000 miles of your typical-sized (8.5 inch) photos. That would nearly take you around the circumference of the globe, twice.

However, I suppose it is truly hard for us (being small humans) to imagine how big the Earth is. That’s like telling an ant to imagine how big the Atlantic Ocean is. The whole thing isn’t in his line of sight, so how is he supposed to really KNOW?

If you’re feeling like the ant, we can relate it to something you are more familiar with. You likely listen to music periodically throughout your day. Now imagine music playing all day every day, for the rest of your life. That seems like it would be a lot of music. But it’s not, in comparison to a petabyte. A petabyte of songs would play continuously for 2,000 years. So, to listen to a petabyte of data, you would have to spend your whole life listening to music, all the time…and then be reincarnated 24 times.

Still having trouble comprehending? Well then we can relate it to something you’re even more familiar with: your own brain. One petabyte is roughly the equivalent of 800 human’s memories. This means that the capacity of your memory is roughly 1.25 terabytes. But don’t feel bad…this is actually A LOT of data (meaning your brain retains a great deal of data/information in a lifetime). It just may not seem like it is when you consider that Walmart would need roughly 2,000 of you to retain all the information that is contained in their databases.

So maybe this is actually why they call it Big Data.

Wednesday, October 21, 2015

Back To The Future With Big Data

With today being “Future Day” due to October 21, 2015 being “the future” in the movie Back To The Future directed by Robert Zemeckis, it has got me thinking about Big Data and the future.

Without Big Data would we have achieved many of the predictions of the future made in the Back To The Future movie? 

Where will Big Data take us by 2030? 

With Big Data infiltrating most industries these days, we can bet that it will greatly effect the way we live by 2030. Healthcare is being revolutionized with better patient records, communication between hospitals and the CDC to control the spreading of epidemics, and even the race to cure cancer s being aided by big data. Transportation is evolving with better taxi apps and the beginning of self driving cars. Our own homes are even being upgraded by big data, with an improving real estate system and the ongoing progress in the idea of a “connected home”.

These are just a few of the different areas Big Data is making an impact, so what does this mean for our future?

What will daily life be like?

Are our jobs going to be taken over by computers?

My predictions for 2030 are as follows,

  1. Doctors will have access to thousands of patient records with the touch of their finger. There will be a digital library that can analyze symptoms and present multiple similar cases, the steps taken and the percentage of positive outcome. This will decrease the amount of tests needed to diagnose symptoms and ultimately save the patient a lot of money and the doctor a lot of time.
  2. Houses will be equipped with smart devices that communicate with one another to save energy and control routine actions such as turning a light on or off automatically. Houses will be able to tell when the owner is about to be home and automatically kick on the heat or air, turn on the lights, unlock the doors and who knows they may even make you  cup of coffee!
  3. Transportation will be drastically improved with self driving cars and more efficient taxi services such as Uber. Uber will be able to track a frequent customer’s debit transactions to know when they close out a tab close to closing time in a bar. This will allow the Uber driver to be outside of the bar and ready for when the customer stumbles out.
  4. Shopping will be more than likely completely different. With the way large stores track consumer habits I wouldn’t be surprised if the stores could communicate with our smart homes to determine which foods or household products we are low on and automatically deliver them to our front door by most likely a drone.

Does this mean we are going to start losing our jobs to automated technology? Yes and no. Sure some jobs will be taken over by computers because it makes the most sense, it is most efficient. That doesn’t mean everyone is going to be out of work. All of these technologies and programs must be monitored and serviced. I think in the next fifteen years we are going to see a major shift in our educational departments towards more technological training. We will need to have more people who are proficient in the new technologies to keep up with any of them. There will be a lot of jobs created to both monitor and service these technological advances.

Will any of this happen by 2030?        Will it happen at all?

 Who knows, but humans have never ceased to amaze me with their ability to create new and exciting things.

Let us know what you think, where will our world be in 2030?

Happy Future Day!!! 

Tuesday, October 20, 2015

Can Big Data Help You Avoid The Flu?

Around this time every year we start to see signs around our local pharmacy and ads on the TV urging everyone to get their flu shot. How important is the flu shot and how does it work?

Big Data Meets CDC

The flu is a highly contagious respiratory illness that affects the nose, throat and lungs. It is an extremely unpleasant illness that can range from mild to fatal. The flu is also a very smart virus that adapts to previous vaccines and forms new strands to survive. It is because of these transformations that the Center for Disease Control and Prevention must produce a new vaccine every year.

In order for the CDC to make new vaccines that are customized to the upcoming flu virus they must know what to protect against. This is where Big Data comes in. The CDC receives about 700,000 patient symptom reports a week. They take these symptoms and analyze them to determine where the  previous vaccine failed and pinpoint the virus’s new strands.

This sort of data also allows the CDC to predict when the peak of flu season is and who is most vulnerable to the virus. Past seasons have shown that flu season is typically from November to March but has shown to peak in February. The data has also shown that elderly people or people with certain immune disorders are most likely to catch the nasty virus. This information is extremely valuable in keeping this illness contained. Big Data allows the CDC to keep up with the virus and do its best to protect people from getting sick.

Thanks to the communication between hospitals and the CDC we can keep down the number of flu cases and hopefully maintain a healthier population.

To read more about how Big Data is aiding in the field of healthcare check out this article on The Patient To Doctor Ratio In Today’s Hospitals.

Big Data Helps To Revolutionize Farming

Farming is no longer about the biggest tractors and cultivators that can cover the most area- it is now a technological race between manufacturers of who can create the highest tech machinery. These machines are revolutionizing big farming, field by field, and big data is entering the farming industry full force.

There are currently machines that have steering assisted by satellite, can download data about crops and soil straight to agronomists and farm managers, work 24-7, and can link with ground sensors and drones to tell within a square meter the size of a field and where the most fertile or waterlogged places are. Even better? It’s comfortable! By allowing these farmers to spend more time analyzing the field than driving, as well as adding the hugely important aspect of big data, farming is becoming more efficient than ever before.

This machine mentioned above (the T8.435) is just the beginning of a very big change that is happening to the farming industry across the world. Soon enough, a a farm manager will be able to live and work in Germany, run machines in England, download weather data from the US, and sell the produce on the global market.

The amount of data that these machines are able to gather is nothing short of amazing. Examples of uses for this abundance of data are identifying which weeds are where in a field, measuring the crop as it is being cut, mapping fields, identifying where fertilizer is needed, and so on.

These machines that are continuously improving are doing to the farming industry what every business today wants: saving both time and money.

It’s simple. The technology has made for better farming.

Big data, machinery, climatology and agronomy are all combining to increase productivity and reduce labor costs. Now farmers have access to data that they never had before. They can measure everything rather than taking straight samples. This is all saving both time and labor, and aiding the people rather than simply replacing them.

I wonder what data the technology will bring next!

Big Data Helps To Predict Storms and Weather Patterns

Big data is playing a major role in predicting severe weather storms, helping weather experts to better understand the storms as they form and approach land. Data has been helping weather experts for many years now, but the smarter the data has gotten, the more accurate the predictions have become.

The speed of prediction and availability of new data sources are making this all possible. For previous large hurricanes in the last 3 years, weather experts have been able to gather the data needed and give the cities around 5 days warning- 5 more days than we had 100 years ago.

Super computers have been built that bring all of the data, whether it be from weather stations, aircrafts, or satellites, together to run against different weather models and predict almost exactly where the storm is going to be.

Although predictions of larger weather patterns are the biggest concern, these systems are also able to look at things like lightning patterns to warn people that may be outside for a specific event on that day.

Researchers are also using these super computers to not only save lives with their predictions, but also improve the quality of life. They are doing so by looking at things like tropical convection and monitoring El Niño and La Niña. Modeling what impact these will have on the weather goes on to improve our quality of life on a daily basis.

Unfortunately, we are not at the point where big data can stop these storms in any way, shape or form as they will run in whatever direction and with whatever force Mother Nature desires. With that said, however, it can help us to prepare for the damage that may come with; and any preparation can save not only a huge amount of money, but also a number of lives.

Could Big Data Help Us Prevent World Hunger?

I recently read an article titled, “How Big Data Will Feed the Global Population- However Big it Gets.” I read the title, an immediately it sparked thoughts of horror. For one thing, it is terrifying to think about what happens if/when the world’s population gets too large for us to handle. Also…what does this mean? How can Big Data be related to our food?

Thus far the Earth has been giving and giving and giving to humans, but surely this cannot last forever. Some argue that we have experienced shortages, and agriculture has not always been as reliable and giving as we would hope (think about North Korea, and China’s great leap forward). But these occurrences, first and foremost were overcome. Additionally, I would argue that they were a result of the shortcomings of man, not the shortcomings of the Earth. If man acts optimally, then the agriculture does too.

More recently, with the help of technology, our ability to cultivate food has grown through the roof. But as our population keeps growing and growing, our ability to cultivate more and more must grow too.

Previously, I was skeptical about this connection, and didn’t understand how big data could really help us in the agricultural arena. For this reason, the author of the article received some negative feedback. People called her out for not being a “gardner.” This may be true, but I have seen that when it comes to big data, it is not industry specific. Here, at Cliintel, We always say, “Everyone is in the Big Data industry.” Now I see that this may be true…even in the agricultural space. You may be wondering “how?”

Well, lets think about what exactly big data does for us. In marketing, it allows us to gather information about individuals, that leads to insights as to what we can do to attract them as customers. It allows us to customize the experience for each person. We can use data to customize virtually anything to a particular person, group, organization or community. We can customize the perfect supply chain management system to a particular company. We do so by taking all aspects of the supply chain into consideration. For example, we can answer the following questions, using data mining and data analysis: who are the best suppliers for our organization? What products do we need from them, and how many at any given time? How often should we take inventory? How much do we need in stock in December? How much do we need in April?

Essentially, big data works the same way in agriculture; It allows us to customize.

In the agricultural world, this is called precision agriculture. You may be wondering, “what is precision agriculture?” It is essentially a mix between big data and robotics that allows for farmers to customize the cultivation of every square foot of their land.

But instead of asking questions about suppliers and inventory, they ask questions about land. Farmers can gather data about soil, air quality, crop maturity, labor costs and equipment costs. Using predictive analytics, and the insight gained from their data, farmers can make better, smarter decisions, that reduce inefficiencies. They waste fewer pesticides, use less water, less energy and ensure greater worker productivity.

Wondering specifically what they can find out? They can see what crops work best in what fields, during what time of year. They can even determine what fertilizers work best for what crops and how much they should use. Using sensors in the soil, that report their readings via GPS, crops can “tell” farmers exactly how much fertilizer they need. They can even tell us their nitrogen and water requirements.

This is all pretty great, and greatly reduces inefficiencies. However, as of now, only about 20% of farms are using precision agriculture technology. In the United States at least. But about 60% of farms in the UK are…looks like we have some catching up to do.

By reducing these inefficiencies, we can get the most out of all the land that we have available. But, the amount of available land will not increase; the Earth will not get bigger. But even then, won’t there come a time when even this wont be enough?


To see the article discussed in this post, click here.