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Monthly Archives: October 2015

Big Data Podcast Conversation With A Big Data Detective

31 Saturday Oct 2015

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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!

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

31 Saturday Oct 2015

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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!

What Do Big Data And Aliens Have In Common?

31 Saturday Oct 2015

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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

31 Saturday Oct 2015

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

Cliintel Big Data Company Helps Habitat For Humanity

30 Friday Oct 2015

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“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?

30 Friday Oct 2015

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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!

3D Printed Hair Club For Men

30 Friday Oct 2015

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3D Printed Hair

Here’s a new technique for 3d printing soft strands, fiber and bristles using fused deposition modeling…

Order your own custom 3d printed hair style. Choose your favorite color too!

Very funny!

3D Printed Hair Club For Men

Get Your 3D Printg MBA!

3D Printing MBA Business Course

The Scary Amount Spent On Halloween

29 Thursday Oct 2015

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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

29 Thursday Oct 2015

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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?

29 Thursday Oct 2015

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play-309042_1280


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

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