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Edward Meinert

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#bigdata  Myth Busting
In this video, Yusuf Ermak addresses some big data myths.  To learn more about Yusuf and his insights, register for Big Data for Health.
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Ritesh Sanghani

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How data entry can help companies to establish a quick and secure database? Learn more at http://goo.gl/3hxyBO
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This is an interesting article recently published in Forbes. The author gathered data from Glassdoor.com, to rank companies. Glassdoor.com is a website where employees make comments about, and rate their company, and can even post their job title and salary range. Keep in mind that the author is not a statistician, and his analysis is based on user-generated content, which, like all reviews, can be fake. Yet the author removed companies with less than 10 reviews, to make this table more robust. So if your start-up is not listed, it's not because it's not in the top, but because there are too few ratings to make a sound conclusion about it.
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G Ignatius

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Baid Own

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Astrophysicists prepare weather forecasts for planets beyond our solar system http://bit.ly/1Jsop8J
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Karim
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Hitesh Mistry

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How to Save Time, Cost and Resources by Outsourcing Your Data Entry Work? Learn more at http://goo.gl/L3FuvE
Tweet Tweet Time is money – We live in an age where things change in blink of an eye; hence the task needs to be performed exceptionally quickly. Lethargic work or procrastination can cost you a good chuck of your fortune. And data entry get no exemption from this worldwide scenario. In this era, when …
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Andy Moses

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With data we drive: KPIs optimizing reporting, for actual performance improvement.
http://bit.ly/KPIs-optimizing-reporting
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Why AtomicDB is "the" Future....

Here are a few points. All NoSQL systems are not ‘Associative Technologies’ in the way we are. Their definition of associative involves the fact that a subject is connected to an object through an association (predicate). “Billy loves cheese” for example whether in a triple “A” -> “B” -> “C”, or an XML: (simplified)

<ENTITY> Billy

            <ACTION> Loves

                        <ENTITY> Cheese

These are considered ‘associative' because a piece of data is connected to another piece of data through another piece of data.  

The fact is they are ‘associative' at the data level. But the are not associative at the storage level, in other words they are not 'Associative Technologies’. They are at best an associative layer on top of an old technology.  

Every statement, triple, K-V pair, is still stored in some hiding system, where the structure and namespace are in between the user and the information.  

For instance to understand that Billy has a relationship with cheese, someone has to know what kind of relationships Billy has with everything. Then one has to search through all the relationships Billy has. Then one has to decide what is pertinent to the interest one has in Billy. Once one gets all the relationships Billy has with the Universe, then one must check each thing’s relationships to find out if anything has relationships to something related (possibly several degrees away) to the said interest in Billy. 

In a real 'Associative Technology’, one which is associative on all levels, (storage, data, information, intelligence, user), one need only select one’s interest area and Billy. The network of relationships, (that in fact are the ‘Associative Technology’), are live, accessible directly and generically from each data element, and, (since everything is automatically contextualized upon ingestion, generating a virtual contextual graph of all minimal pathways between all contexts (not at the data level like all NoSQL systems)), can provide an automated means to answer every question one can ask about anything. In every other ‘technology’ you can only find what you specifically ask for in a unique namespace bound query created in some complex language like OWL or SparQL… "What does Billy Love?" one could ask and in the result set one would find cheese, but Billy could ‘like’ of ‘enjoy’ or ‘really like’ or 'is enamoured with’ or ‘adores’ or ‘whatever’ cheese. How could one possibly know what to ask to find out that there is some sentiment with cheese. One would need to encode some ontology to deal with the ideas of sentiments, affective states, and proclivities as well as foods, food groups, dairy products, etc, to begin with. Then comes the taxonomies… 

What if the interest was farms, and one wanted to know if Billy has any interest in farms. The knowledge of farms, farm products, distribution networks and grocery stores would have to be factored into the data store, and intelligently presented so that a query could path it’s way from Billy to the farm, through his love of cheese. 

 In our system, (we have an Associative Information System, that mimics human memory capabilities. It can function as a database but calling it a database is like calling a human a consumer, sure a human can consume but there is far more to being human that just consuming, (or at least one would hope), all relationships are facts and all relationships are in dimensions of association that correspond directly to the many and varied contexts of the information about the data. Finding common information about  any number of things is simply part of the associative memory function capabilities of the system. It ‘resolves’ relationships in a completely general and generic (non-namespace bound) way.

 

Just the beginning... .

Dr Ron Everett 
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these are the main points that everyone ignores. and assumes are part of everything (SQL or NON-SQL) .. the idea is to convey that that is not the case..  if any of these limitations are on the technology you are using.. then the argument stops there.. Until anyone can provide me with a system that has no Duplicates at all.. they are the lesser of the two points of view..  and to be clear.. getting lost in the  formatting vs the message is also non productive..  like worrying about how you are going to drive somewhere without having a car.. ;-)
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Baid Own

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Jupiter's Frozen Ocean Moon Could Hide Life http://bit.ly/1KIx8Su
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Guido Stepken

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Big data and weather forecast. A billion dollar business.


Imagine tomorrow there would be no weather!?? 
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Python & data analytics go hand in hand. Here is a list of 9 Python data analytics libraries. This list is going to be continuously updated here.
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prasad k

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Registering for this site is easy. Just fill in the fields below, and we'll get a new account set up for you in no time. Account Details. Username (required) Email Address (required) Choose a Password (required). Confirm Password (required). Profile Details. Name (required) ...
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I asked myself this question a few months ago. Next I thought: What is the definition of Data Science? So the first thing I started to do is read as many posts on the topic as I could get my hands on and also lookup definitions of related topics such as Data Mining and Machine Learning. Looking at the discussions and posts around Data Science it seems to span everything needed to understand data, to derive something out of data and communicate the finding. This does not really help to answer the original question, so let´s take a closer look.
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Very interesting!
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One of the most discussed topics in healthcare today is Cancer. Hundreds of companies work hard to invent new diagnostic methods, offer new treatment options and develop tests that can help monitor this nasty disease. Recently I was looking for latest clinical trials in breast cancer for my work project and found an awesome public clinical trial registry supported by NIH. The ClinicalTrials.gov currently lists about 190,000 studies conducted across the US and around the world.
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The  moment I picked the book..."The Handbook of Data Science" I sensed that this would be different and profoundly impact me.  I must confess that, my understanding of this beautiful art/science of drawing insights from data has gone up to a whole new level.
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For those coming in late, IoT is the network of physical objects or "things" embedded with electronics, software, sensors and connectivity to enable it to achieve greater value and service by exchanging data with the manufacturer, operator and/or other connected devices. Each thing is uniquely identifiable through its embedded computing system but is able to interoperate within the existing Internet infrastructure.
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Haha yes, exactly! I don't intend to give online marketers even more information about my daily habits ;) 
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Gregory Mooney

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In this video blog, Paul Bruce had a chance to chat with Kin Lane, API Evangelist, about how the increase in API surface area is being addressed from a security perspective.
Learn how API's are shaping cities with Paul Bruce's Coverage of 2015 APIdays Mediterranea. API's, IoT, and Hypermedia are discussed in this video.
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