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7 More Big Data Companies to Watch

7 More Big Data Companies to Watch | Complexity | Scoop.it

Like any market in its infancy, the big data industry is bustling with companies jockeying for a comfortable position in a niche that is as surefire as any.


Via Luca Naso
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Luca Naso's curator insight, June 29, 2015 10:18 AM

Here is a list of 7 "new" companies that might make the difference in the realm of Big Data.

 

1. Palantir Technologies

Founded in 2004 and evaluated at $20B it is probably not a startup anymore

2. Crayon Data 

Big data for decision making

3. Neo Technology

Best known for its graph db Neo4j

4. Couchbase

The company behind the NoSQL db Couchbase server.

5. PromptCloud

Specialised in Data-as-a-Service

6. Snowflake

Big Data technologies for SMBs.

7. Saama Technologies

Is this a startup? Founded 18 years ago, it has clients such as Apple and Cisco

Glenn Wallace's curator insight, June 30, 2015 11:18 AM

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iSparkCEO's curator insight, August 4, 2015 2:30 PM

Here is a list of 7 "new" companies that might make the difference in the realm of Big Data.

 

1. Palantir Technologies

Founded in 2004 and evaluated at $20B it is probably not a startup anymore

2. Crayon Data 

Big data for decision making

3. Neo Technology

Best known for its graph db Neo4j

4. Couchbase

The company behind the NoSQL db Couchbase server.

5. PromptCloud

Specialised in Data-as-a-Service

6. Snowflake

Big Data technologies for SMBs.

7. Saama Technologies

Is this a startup? Founded 18 years ago, it has clients such as Apple and Cisco

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How Applications of Big Data Drive Industries

How Applications of Big Data Drive Industries | Complexity | Scoop.it
How industries like banking, healthcare, education, manufacturing, Insurance, retail, etc. are using big data.

Via Luca Naso
David Urpani's insight:

Time to talk less about Big Data and more about its beneficial applications!

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Fabio Di Pasquale's curator insight, April 5, 2:30 AM

There is a substantial spending on big data, with more than 75% of companies (from different industries) investing in big data in the next two years.

 

Each industry vertical has its own challenges and solutions. Here is a great article and infographics by simplilearn that describe for 10 verticals both main challenges and applications.

The 10 industries are:

1. Banking

2. Communication

3. Healthcare

4. Education

5. Manufacturing

6. Government

7. Insurance

8. Retail

9. Transportation

10. Energy

Emeric Nectoux's curator insight, April 22, 3:29 AM

A Gartner Survey for 2015 shows that more than 75% of companies are investing or are planning to invest in big data in the next two years. These findings represent a significant increase compare to 2012.

Hobiana Rakotonirina's curator insight, November 7, 7:28 AM

There is a substantial spending on big data, with more than 75% of companies (from different industries) investing in big data in the next two years.

 

Each industry vertical has its own challenges and solutions. Here is a great article and infographics by simplilearn that describe for 10 verticals both main challenges and applications.

The 10 industries are:

1. Banking

2. Communication

3. Healthcare

4. Education

5. Manufacturing

6. Government

7. Insurance

8. Retail

9. Transportation

10. Energy

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Interview: Prof Geoffrey West on complexity science

CLC interviewed Prof. Geoffrey West, Distinguished Professor and Past President of Sante Fe Institute, at the World Cities Summit 2014 on the study of cities in relation to complexity science....

Via Roger D. Jones, PhD
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Complexity Science: An Introduction

Facebook: https://www.facebook.com/profile.php?id=100004910296787 Complex systems present problems both in mathematical modelling and philosophical foundations. The study of complex systems...
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Crowds, Icons & Tribes = The Next Marketing

Crowds, Icons & Tribes = The Next Marketing | Complexity | Scoop.it
Crowds, Icons & Tribes
The more we work our Startup Factory Funded statup http://www.Curagami.com the more every client needs a combination of :
* Crowds.
* Icons.
* Tribes.
Crowds bring wisdom.

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Wisdom Of Crowds® Business Intelligence Market Study

Wisdom Of Crowds® Business Intelligence Market Study | Complexity | Scoop.it
Be Part of the Crowd - Wisdom of Crowds® Business Intelligence Market Study

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AI Emergent Behavior.mp4

An demonstration of emergent behavior and complex system interaction using C#.
David Urpani's insight:

A great (and topical) example of complex, emergent behaviour from a set of agents following simple rules.

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The Emerging Science of Superspreaders (And How to Tell If You're One Of Them)

The Emerging Science of Superspreaders (And How to Tell If You're One Of Them) | Complexity | Scoop.it

Who are the most influential spreaders of information on a network? That’s a question that marketers, bloggers, news services and even governments would like answered. Not least because the answer could provide ways to promote products quickly, to boost the popularity of political parties above their rivals and to seed the rapid spread of news and opinions.

 

So it’s not surprising that network theorists have spent some time thinking about how best to identify these people and to check how the information they receive might spread around a network. Indeed, they’ve found a number of measures that spot so-called superspreaders, people who spread information, ideas or even disease more efficiently than anybody else.

 

But there’s a problem. Social networks are so complex that network scientists have never been able to test their ideas in the real world—it has always been too difficult to reconstruct the exact structure of Twitter or Facebook networks, for example. Instead, they’ve created models that mimic real networks in certain ways and tested their ideas on these instead.

 

But there is growing evidence that information does not spread through real networks in the same way as it does through these idealised ones. People tend to pass on information only when they are interested in a topic and when they are active, factors that are hard to take into account in a purely topological model of a network.

 


Via Ashish Umre
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AI Emergent Behavior.mp4

An demonstration of emergent behavior and complex system interaction using C#.
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David Urpani's curator insight, July 13, 2014 6:21 PM

A great (and topical) example of complex, emergent behaviour from a set of agents following simple rules.

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6 Tech Predictions To Have A Major Impact In 2016

6 Tech Predictions To Have A Major Impact In 2016 | Complexity | Scoop.it
6 Tech Predictions To Have A Major Impact The technology industry moves at a relentless pace, making it both exhilarating and unforgiving.

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Ante Lauc's curator insight, December 10, 2015 9:02 AM

I like such expectation...

Eric Redegeld's curator insight, December 16, 2015 3:08 PM
1. The death of the password is rapidly approaching -  Developers need to evaluate security solutions that are able to apply contextual identity, adaptive risk and multi-factor authentication at authentication plus at any point throughout a session. This kind of continuous security approach will be embraced in the marketplace and become the new standard, because it ensures authenticity of users, devices, things and services at all times and can mitigate risk whenever an anomaly is detected, even during existing sessions.  2. Chip to cloud (or device to cloud) security protection will be the new normal -  With most data chains now spanning the full spectrum of chip, device, network and cloud (plus all stages in between), many organizations are starting to realize a piecemeal approach to protection simply isn’t effective. This realization is spurring the adoption of more ‘chip to cloud’ security strategies, starting at the silicon level and running right through to cloud security. In this model, all objects with online capabilities are secured the moment they come online, meaning their identity is authenticated immediately. In doing so, it eliminates any window hackers have to hijack the identity of unsecured objects, thus compromising the entire data chain via a single entry point.   3. New technologies and standards that enable consumer privacy and security will become a competitive differentiator  -  They’re thinking of how to build delegation and consent capabilities fast enough to satisfy their customers, the business and the ever changing regulatory landscape. And they know they must do all of this with an architecture that scales to support millions of consumers and employees that can manage their own permissions.  User Managed Access (UMA) makes this all possible. UMA is now becoming available and can deliver this kind of experience. Those who embrace it early will be able to build a far stronger relationship with customers built on trust and mutual benefit.  4. The evolving Internet of Things will change the way we interact with the world around us - This is about to change. As technology evolves and contextual big data becomes more meaningful, businesses and governments will be able to harness the IoT to fundamentally change our daily lives. Central to this is the increasingly intertwined relationship between people, ‘things’ and apps, meaning things like medical devices, thermostats, security cameras and cars are able to receive a constant stream of personalized information straight to their device.  Key elements of the smart city concept are based on the ability to, for instance, use sensors connected to traffic lights to ease congestion, or use earthquake monitoring to shut down gas lines or other critical infrastructure that could be damaged in a quake. Securing systems such as these will be critical to public safety, and digital identity will be the critical security layer as smart cities get built out.  5. Tagging data at source will multiply the value of big data exponentially - In order to make sense of big data, it must be examined within the context it was collected. By tagging data at the point of collection with additional contextual information, the value that can be extracted from it across an organization is multiplied significantly. Key factors such as where and when the data was collected or who/what it was collected from are central to understanding data more effectively.   6. The fight to become the “Amazon of the IoT” will intensify - As the IoT’s vast potential becomes more apparent, we will start to see a growing number of organizations fighting to establish themselves as the go-to provider of IoT solutions, or the Amazon of the IoT. This will spur the rise of the IoT mega-platform; vast one-stop-shop Platform-as-a-Service solutions. The battle will likely play out across both the consumer and enterprise spaces and many of the usual suspects are already coming to the fore. Apple, Google and Intel are all vying for control of our homes, while Microsoft, IBM and Oracle are fighting over our businesses, 
MCH's curator insight, December 30, 2015 2:48 PM

Great 

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Entropy | Special Issue : Information Processing in Complex Systems

All systems in nature have one thing in common: they process information. Information is registered in the state of a system and its elements, implicitly and invisibly. As elements interact, information is transferred and modified. Indeed, bits of information about the state of one element will travel—imperfectly—to the state of the other element, forming its new state. This storage, transfer, and modification of information, possibly between levels of a multi level system, is imperfect due to randomness or noise. From this viewpoint, a system can be formalized as a collection of bits that is organized according to its rules of dynamics and its topology of interactions. Mapping out exactly how these bits of information percolate through the system could reveal new fundamental insights in how the parts orchestrate to produce the properties of the system. A theory of information processing would be capable of defining a set of universal properties of dynamical multi level complex systems, which describe and compare the dynamics of diverse complex systems ranging from social interaction to brain networks, from financial markets to biomedicine. Each possible combination of rules of dynamics and topology of interactions, with disparate semantics, would reduce to a single language of information processing.

 

Guest Editor: Dr. Rick Quax

 

Deadline for manuscript submissions: 28 February 2015


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Cell communication: Stop the microbial chatter - Nature.com

Cell communication: Stop the microbial chatter - Nature.com | Complexity | Scoop.it
Cell communication: Stop the microbial chatter
Nature.com
To undermine the microbes' language, scientists first need to work out what they are saying. Bacteria use chemical signals to synchronize behaviour across a population.
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Online Communities: Oh, a Wise Guy, Eh?

Online Communities: Oh, a Wise Guy, Eh? | Complexity | Scoop.it
New research suggests a path for online communities beyond the wisdom of the crowds. Also: what happens when your brand voice loses its consistency.

Via Thomas Faltin
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A Closer Look at Transformation: Collective Intelligence

A Closer Look at Transformation: Collective Intelligence | Complexity | Scoop.it

Next up in this transformation series is the seventh enabler: Collective Intelligence. One of the key themes throughout this transformation series is the clear movement from an enterprise entity to an extended enterprise of stakeholders. This extended enterprise – or what I alternatively call value ecosystem – increases complexity and requires a new management approach to be effective. I use the term collective intelligence as an umbrella phrase that combines the critical need for both collaboration and analytic excellence. This includes other forces like crowd computing, crowdsourcing, co-creation, and wisdom of the crowd – all of which stem from the connectedness of our world, and the growing realization that value creation requires a broader community.

 

 


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How languages evolve - Alex Gendler

How languages evolve - Alex Gendler | Complexity | Scoop.it
Over the course of human history, thousands of languages have developed from what was once a much smaller number. How did we end up with so many? And how do we keep track of them all? Alex Gendler explains how linguists group languages into language families, demonstrating how these linguistic trees give us crucial insights into the past.

Via Ashish Umre, Complexity Digest
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Introduction to Complex Systems: Patterns in Nature

This video provides a basic introduction to the science of complex systems, focusing on patterns in nature. (For more information on agent-based modeling, visit http://imaginationtoolbox.org ).


Via Lorien Pratt, Complexity Digest
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António F Fonseca's curator insight, February 1, 2014 4:50 AM

Agent based modeling still is the best tool to understand complex systems when mathematical modeling gets very complicated.

Liz Rykert's curator insight, February 10, 2014 7:25 PM

Always looking for good resources to introduce complexity science to others. This looks great. 

Ian Biggs, FAIPM, CPPE's curator insight, April 16, 2014 8:08 PM

I recently conducted a series of workshops on the subject of 'Complex Project Management - Navigating through the unknown'. This clip provides a great introduction to complex systems and for those interested in Complexity Science, this clip is worth 7:52 of your time.