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Rescooped by Edward Chenard from Big Data Technology, Semantics and Analytics
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Technology And BIG Data Are Changing The Retail World - Forbes

Technology And BIG Data Are Changing The Retail World - Forbes | Big Data and Personalization | Scoop.it

Via Kun Le, Tony Agresta
Edward Chenard's insight:

And we are at the forefront of this.

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Tony Agresta's curator insight, January 29, 2013 10:20 AM

The conclusions in this article are spot on.


  • Streamline data and data gathered for you by market researchers
  • Help you manage, tabulate, analyze, visualize and deliver data in interactive, web-based and mobile formats
  • Provide insight into your target market
  • Offer solutions to pressing business problems.


The only one I would add would emphasize the need to use ALL of your data including new forms of unstructured data created through social and mobile.  Streaming this data in real time allows retailers to react to advertising, sentiment, changes in buying behavior and more.

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Rescooped by Edward Chenard from BIG data, Data Mining, Predictive Modeling, Visualization
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The power and promise of Analytics: Three case studies « Big Data Made Simple

The power and promise of Analytics: Three case studies « Big Data Made Simple | Big Data and Personalization | Scoop.it
The following are examples of analytics applied in network security, healthcare and education. Each will discuss the data that is used, the process by which the data is reviewed and an algorithm is derived, the application of the algorithm, the risks raised and how they are mitigated, and how the

Via AnalyticsInnovations
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Rescooped by Edward Chenard from Designing design thinking driven operations
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Why Internal Branding is Central to Customer Experience Management

Why Internal Branding is Central to Customer Experience Management | Big Data and Personalization | Scoop.it

Why Internal Branding is Central to Customer Experience Management (RT @clearaction: Why Internal Branding is Central to Customer Experience Management http://t.co/ghRsVQFQrL #CX #customer #experience)...


Via Fred Zimny
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Rescooped by Edward Chenard from Strategy and Competitive Intelligence by Bonnie Hohhof
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Bursting the Big Data Bubble: The Case for Intuition-Based Decision Making (book)

Bursting the Big Data Bubble: The Case for Intuition-Based Decision Making (book) | Big Data and Personalization | Scoop.it

Jay Liebowitz, editor. (From the preface.)The contributors emphasize the importance of applying intuition, gut feel, spirituality, experiential learning and insight as key factors in a executive’s decision-making process. As we get caught in the quagmire of big data and analytics, it is important to be able to reflect and apply insights, experience, and intuition as part of the executive and managerial decision-making process.

 


Via Bonnie Hohhof
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Rescooped by Edward Chenard from digital marketing strategy
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How Facebook Calculates What Appears In Your News Feed

How Facebook Calculates What Appears In Your News Feed | Big Data and Personalization | Scoop.it
With Facebook organic reach destined to reach zero percent sooner or later, what can savvy business owners do to amplify their Facebook results now?

Via malek
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malek's curator insight, July 18, 12:52 PM

The 12 practical tips is how you can make use of the above analysis

Rescooped by Edward Chenard from Big Data
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Why Data Visualizations Provides You a Competitive Edge

Why Data Visualizations Provides You a Competitive Edge | Big Data and Personalization | Scoop.it

Tableau Software develops data visualizations that provide insights from Big Data in an easy to understand manner, giving you a competitive edge.


Via Vanrijmenam
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Why the Internet of Things Data Will Spark an IT Revolution

Why the Internet of Things Data Will Spark an IT Revolution | Big Data and Personalization | Scoop.it
It seems the Internet of Things is teaching Big Data humility.

Via EMC Education Services
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Rescooped by Edward Chenard from Strategy & Governance
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Wanted: Big data unicorns to wrangle unruly data !

Wanted: Big data unicorns to wrangle unruly data ! | Big Data and Personalization | Scoop.it
Big data skills remain hard to find, and confusion about how to define what a data scientist does is just adding to the headaches.

The skills needed to wade through the rising tide of big data are in short supply, according to employers, although their unrealistic expectations may be part of the problem of finding the right staff.

On top of this, managers said they found it hard to explain their needs to HR managers and recruitment agencies, and to assess the skills of candidates...


Via Fouad Bendris
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Fouad Bendris's curator insight, July 11, 12:58 PM

However, it admits that this is a rare set of abilities. "Some say that looking for them is like 'chasing unicorns', because people able to master all those skills are so rare, while others complain that the data scientist label has become too vague a description of an occupation to be useful."

 

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Six tips for using Big Data to wipe out cyberthreats

Six tips for using Big Data to wipe out cyberthreats | Big Data and Personalization | Scoop.it
You need to be smart about harnessing big data to defend against today's security threats, data breaches, and attacks

Via cysap
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Rescooped by Edward Chenard from What is Data Science
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Big Data Survey Finds 75% of Businesses Yet to Reach Production - insideBIGDATA

Big Data Survey Finds 75% of Businesses Yet to Reach Production - insideBIGDATA | Big Data and Personalization | Scoop.it
Big Data Survey Finds 75% of Businesses Yet to Reach Production

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Carla Gentry CSPO's curator insight, June 17, 8:31 AM

Yes, businesses are more committed to implementing big data analytics than ever before, but, far too many are still struggling with how to maximize the benefit,” said Drew Rockwell, CEO of Lavastorm. “These survey results underpin how investing in analytics is just the first step. It’s organizations that go the next level by removing complexities from the analytics process and empowering others in the organization, namely business analysts, that are going be able to turn data insights into actionable business enhancements for long-term success.”

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The Modern Data Nerd Isn’t as Nerdy as You Think | Enterprise | WIRED

The Modern Data Nerd Isn’t as Nerdy as You Think | Enterprise | WIRED | Big Data and Personalization | Scoop.it
Data scientists are fast becoming the rock stars of the 21st century. Thanks in part to Nate Silver's eerily accurate election predictions and Paul DePodesta's baseball-revolutionizing Moneyball techniques, math nerds have become celebrities. It's debatable how much their work differs from what statisticians have done for years, but it's a growing field, and many companies are desperate to hire their own data scientists. The irony is that many of these math nerds aren't as math nerdy as you might expect.

Via Carla Gentry CSPO
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Carla Gentry CSPO's curator insight, June 15, 9:04 AM

No matter what degree they earn, Candido says, data scientists are never done learning. 

Rescooped by Edward Chenard from What is Data Science
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The World Startup Report Releases ‘The Internet Hall Of Fame” With Data From 50 Countries | TechCrunch

The World Startup Report Releases ‘The Internet Hall Of Fame” With Data From 50 Countries | TechCrunch | Big Data and Personalization | Scoop.it
Last March, TechCrunch covered one of the World Startup Report's first releases. Now the organization is back with an ambitious project that gathers insight..

Via Carla Gentry CSPO
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Carla Gentry CSPO's curator insight, June 13, 11:19 AM
29 countries have at least one Internet company worth $1 billion. Unless you have been hiding under a rock, you’ve heard of Google ($410 billion) and Alibaba Group ($200 billion). Lesser known members of the club (at least to readers in the U.S.), however, include search engine Yandex of Russia ($15.8 billion); Israel’s Checkpoint, the security software maker ($13.6 billion); search portal Naver in South Korea ($28 billion); and media companyNaspers in South Africa ($46 billion).
Rescooped by Edward Chenard from Big Data, Cloud Computing, Virtualization
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Predictive data, the real workhorse behind the Internet of Things

Predictive data, the real workhorse behind the Internet of Things | Big Data and Personalization | Scoop.it
Companies are having to be pickier about which data sets they collect, process and use. It's all about having the right architecture in place.

Via EMC Education Services
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Rescooped by Edward Chenard from Designing design thinking driven operations
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Egon Lüftenegger PHD thesis' service-dominant business design

This dissertation integrates different perspectives on service in order to design a framework and toolset supporting business design in service

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Rescooped by Edward Chenard from Strategy and Competitive Intelligence by Bonnie Hohhof
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Big Data Analytics: 80/20 Rule Isn’t Good Enough

Big Data Analytics: 80/20 Rule Isn’t Good Enough | Big Data and Personalization | Scoop.it

Information is nothing if we don’t do something with it. The companies that do invest, implement effective data governance strategies, and leverage the right tools both internal and third-party will be the industry leaders. They won’t settle for the 80/20 rule for driving results from their data. They’ll expect to get results from everything, to save everywhere and enhance the customer experience at all levels. The recent Economist article by Schumpeter points out, this won’t happen by “massive, instant holy grail solutions,” but rather by “lots of small advances.”


Via Bonnie Hohhof
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AnalyticsInnovations's curator insight, July 29, 4:06 AM

A different dialect on the fight of segmentation vs. correlation; is it one or the other?

Momentis Systems's curator insight, July 29, 8:56 AM

"If companies don’t cultivate the seeds of their data, they won’t progress in the next five years."


With the rapid growth of everything 'online' from the Cloud to IoT, companies must take measures to understand not only their data but the path their industries are taking. They need to take a stance to understand in the early stages in order to stay afloat in the coming years. If we think that our data is 'big' now, imagine what it will be like in 5 years! 

Rescooped by Edward Chenard from Content Marketing & Content Strategy
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7 Marketing Diagrams That Explain Content Marketing

7 Marketing Diagrams That Explain Content Marketing | Big Data and Personalization | Scoop.it

When concepts get tough, content gets visual. Marketing diagrams are a fast way to explain interrelated concepts and tricky ideas. Nothing makes a muddy post clear like a good visual.


Via Geoffrey Laloux, Stefano Principato
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Olivier Milo's curator insight, July 26, 12:45 AM

Impressive collection of content marketing diagrams by Andy Crestodina. Thanks!

 

Rescooped by Edward Chenard from Strategy and Competitive Intelligence by Bonnie Hohhof
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The Emerging Clusters Model: A tool for identifying emerging technologies across multiple patent systems

The Emerging Clusters Model: A tool for identifying emerging technologies across multiple patent systems | Big Data and Personalization | Scoop.it

Emerging technologies are of great interest to a wide range of stakeholders, but identifying such technologies is often problematic, especially given the overwhelming amount of information available to analysts and researchers on many subjects. This paper describes the Emerging Clusters Model, which uses advanced patent citation techniques to locate emerging technologies in close to real time, rather than retrospectively.Patents in emerging clusters consistently have a significantly higher impact on subsequent technological developments than patents outside these clusters.The Emerging Clusters Model may be a useful tool for identifying interesting new technologies as they emerge.(academic)


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Rescooped by Edward Chenard from Quantified Self, Data Science, Digital Health, Personal Analytics, Big Data
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Virtual Humans: More Honest Data in the Future of Healthcare | HL7 Standards

Virtual Humans: More Honest Data in the Future of Healthcare | HL7 Standards | Big Data and Personalization | Scoop.it
Virtual Human technology is used to help clinicians understand patients, but new research says it also creates better data because patients are more honest.

Via Tictrac
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Rescooped by Edward Chenard from Content Marketing & Content Strategy
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What People Share On Social Networks

What People Share On Social Networks | Big Data and Personalization | Scoop.it
According to latest Infographic released by GO Gulf Web Technologies, sharing pictures is the most preferred by social media users (46%), followed by Opinions (26%), Status update of what and how the…

Via Stefano Principato
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Stefano Principato's curator insight, July 15, 1:33 AM

Majority of social media users surveyed (78%), share information online because it lets them stay connected to people they may not otherwise stay in touch with.

Joshua McCarty's curator insight, July 15, 11:49 PM

Another great #infographic on how people use #socialmedia

 

Rescooped by Edward Chenard from Consumer Behavior in Digital Environments
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Dropbox's Head of Design on the Dawn of Personalized Products

Dropbox's Head of Design on the Dawn of Personalized Products | Big Data and Personalization | Scoop.it

Cuervo is a firm believer that you need to know where you’ve been before you can decide where you’re going. In this case, it’s important for founders to understand how product personalization in computing has evolved and where it is today so they can decide what their next move should be.

It may be hard to believe that the concept of personalization is as old as personal computing itself, but that’s what skeuomorphic design was all about on the early Macintosh: Folders and files were fashioned to look and operate like their real-life counterparts to ease early adopters into digital work. Obviously since then there’s been a massive jump.

Over the past ten years, consumer technology has gotten to know our names, where we're located, what we’re interested in, and who we’re connected to —both socially and implicitly. It was at the start of this transition that Cuervo entered the scene, joining Facebook right as algorithms were making it possible to give individual users tailored experiences.

 


Via Russ Merz, Ph.D.
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Russ Merz, Ph.D.'s curator insight, July 13, 9:53 AM

An interesting discussion about the four ingredient of personalized digital product design as envisioned by Soleio Cuervo at DropBox. The four components of identity, graphs, context and behavior when combined build personal engagement with consumers.

Rescooped by Edward Chenard from Big Data, Cloud and Social everything
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With Big Data Comes Big Responsibility

With Big Data Comes Big Responsibility | Big Data and Personalization | Scoop.it
“You should presume that someday, we will be able to make machines that can reason, think and do things better than we can,” Google co-founder Sergey Brin said in a conversation with Khosla Ventures founder Vinod Khosla.  To someone as smart as Brin, that comment is as normal as sipping on his super-green juice, but…

Via Pierre Levy
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Unlocking Big Data's Value Potential Through Design with Small Data

Unlocking Big Data's Value Potential Through Design with Small Data | Big Data and Personalization | Scoop.it
Co-written by Finn Birger Lie



Big Data is perceived as the next value opportunity for corporations to innovate and grow. To be of any real value, however, Big Data has to become more accessible and understandable to non-specialist users and leave ...

Via Carla Gentry CSPO
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Carla Gentry CSPO's curator insight, June 23, 8:54 AM

Most organizations do not have terra or petabytes of useful data available to them. However, the most important aspect of Big Data is not so much the volume of a dataset, but more in the insights derived from combining several, dispersed, smaller datasets. More data means more reliable insights but it does not automatically guarantee more insights.

Rescooped by Edward Chenard from Quantified Self, Data Science, Digital Health, Personal Analytics, Big Data
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Convergence of Big Data and Quantified Self

Convergence of Big Data and Quantified Self | Big Data and Personalization | Scoop.it
A deluge of data is changing how we live, how we make decisions, how we shop and how we do pretty much everything else under the sun. However one specific area which is probably experiencing the

Via Tictrac
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The Cardinal Sin of Data Mining and Data Science: Overfitting

The Cardinal Sin of Data Mining and Data Science: Overfitting | Big Data and Personalization | Scoop.it

Via Carla Gentry CSPO
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Carla Gentry CSPO's curator insight, June 14, 10:12 AM

We note that Overfitting is not the same as another major data science mistake - "confusing correlation and causation". The difference is that overfitting finds something where there is nothing. In case of "correlation and causation", researchers can find a genuine novel correlation and only discover a cause much later (see a great example from astronomy in Kirk D. Borne interview on Big Data in Astrophysics and Correlation vs. Causality).

Rescooped by Edward Chenard from Big Data & Digital Marketing
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The Hidden Biases in Big Data

The Hidden Biases in Big Data | Big Data and Personalization | Scoop.it
Blindly trusting it can lead you to the wrong conclusions.

Via Luca Naso
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Luca Naso's curator insight, June 13, 8:11 AM

Big Data can be extremely dangerous without a Big Brain to analyse them properly.


Huge data sets ALWAYS contain some relations: some of them are right (causation), others are simply wrong. It pertains to data analysis to uncover the truth.

 

"As we move into an era in which personal devices are seen as proxies for public needs, we run the risk that already existing inequities will be further entrenched.

[...]

This goes beyond merely conducting focus groups to confirm what you already want to see in a big data set. It means complementing data sources with rigorous qualitative research."

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Why Online Tracking Is Getting Creepier

Why Online Tracking Is Getting Creepier | Big Data and Personalization | Scoop.it
The merger of online and offline data is bringing more intrusive tracking.

Via Carla Gentry CSPO
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Carla Gentry CSPO's curator insight, June 12, 2:19 PM

But online marketers are increasingly seeking to track users offline, as well, by collecting data about people's offline habits—such as recent purchases, where you live, how many kids you have, and what kind of car you drive.