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VC Cash Says,

VC Cash Says, | Data Nerd's Corner | Scoop.it
data technology service providers are getting funded, but until scale through wide adoption by smaller businesses is imminent, don't expect a bubble.
Carla Gentry CSPO's insight:

WTF - You want people with no analytics background to be responsible for your mulit-billion dollar company - Good luck with that!

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Data Nerd's Corner
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Carla Gentry - IBM Insight 2014 - theCUBE - YouTube

Carla Gentry, Analytical Solution,at IBM Insight 2014 with John Furrier and Dave Vellante @theCUBE #ibminsight
Carla Gentry CSPO's insight:

An honor to be interviewed, thanks!

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EBN - Mary E. Shacklett - In Pursuit of Sustainable Electronics

EBN - Mary E. Shacklett - In Pursuit of Sustainable Electronics | Data Nerd's Corner | Scoop.it
Major steps in a corporate sustainability practice include:

Establishing a sound and credible foundation within the company for sustainability
Training sustainability into corporate culture
Communicating with all stakeholders (the board, investors, customers, suppliers, regulators, etc.) about your sustainability practices
Setting sustainability metrics and goals
Working with your supplier base and manufacturing processes
Creating end of life disposal alternatives for electronic components and devices
Carla Gentry CSPO's insight:

In 2013, for instance, Apple conducted a sustainability compliance audit. It uncovered 147 facilities that were not properly storing or handling chemicals, 85 establishments did not compliantly label hazardous chemicals, and 106 suppliers that were not properly disposing of hazardous waste. Thirty-five companies in its supply chain did not efficiently manage and prevent stormwater contamination, while 96 facilities did not sufficiently monitor and control air emissions. This occurred despite Apple requiring suppliers to treat emissions, conduct regular inspections, maintain total legal compliance, and identify avenues of emission reduction.

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The Unanswered Question of How Often Should You Post on Social Media?

The Unanswered Question of How Often Should You Post on Social Media? | Data Nerd's Corner | Scoop.it
There is no general answer to the question how often to post, what is right for one person can be totally wrong for another.

There are so many factors playing important roles that answering the question with a number is totally misleading. So what factors make a difference?

- See more at: http://blog.thesocialms.com/post/98886373476/the-unanswered-question-of-how-often-should-you#sthash.8QIP475q.dpuf
Carla Gentry CSPO's insight:

The size of your account and the activity of your following The amount of content you have to share: Good quality content, here the graphic is right, rather post less often if you do not have enough good content. The social network in question does make a difference… How well targeted is your following? Who is your audience, what do they expect? …

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Are all Software Applications becoming Analytic Applications?

Are all Software Applications becoming Analytic Applications? | Data Nerd's Corner | Scoop.it
Action doesn’t take place inside of applications. The root of all action is in people and their language. This is a valuable perspective offered by Terry Winograd at Stanford. Action exists in the language and narratives of people. Therefore, in designing effective analytics applications, we need to understand people’s intentions, their roles, their capabilities and their social context as part of that context. In Logi’s figure on p.6 of their report all of the arrows need to be bi-directional and the user needs to be represented in a broader context. This is where leaders in this space need to take us.
Carla Gentry CSPO's insight:

So while serving information needs may be "about creating applications that users love” so that they use it – this again is more marketing rhetoric. What to aim at first is the effectiveness of fulfilling people’s and businesses’ intentions. Logi may or may not help you get there.

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It’s 11 PM – Do You Know Where Your Data Is? By @EFeatherston [#Cloud] | SYS-CON MEDIA

It’s 11 PM – Do You Know Where Your Data Is? By @EFeatherston [#Cloud] | SYS-CON MEDIA | Data Nerd's Corner | Scoop.it
Do You Know Where Your Data Is?
In this fast paced, rapidly changing technology environment we live in today, we are providing and collecting huge amounts of data from an ever-increasing number of potential sources, whether they be mobiles, wearables, our vehicles, or any other of a myriad of sources we haven't even thought about. This data is traveling through the nebulous cloud environment we all love to talk about, and traveling through the ether to its final destination. Our challenge as technologists is to understand the implications, challenges, and tradeoffs involved in that world, and be able to articulate those to the business so that the proper balance between business needs, data privacy, convenience, et al, can be achieved. It all starts with that simple question I started with, it's 11pm, do you know where your data is?
Carla Gentry CSPO's insight:

As technologists, we have a responsibility to help the business understand the tradeoffs and risks involved in this rapidly changing environment. We as humans, by nature, love to hoard things, and data is no different. We are accumulating large amounts of data as it passes through our systems. If it is in or passes through your system, you have a responsibility to ensure the rules are followed. 

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Wireless Data Could Travel Twice as Fast Using a New Circuit | MIT Technology Review

Wireless Data Could Travel Twice as Fast Using a New Circuit | MIT Technology Review | Data Nerd's Corner | Scoop.it
The new circuit, known as a circulator, can isolate signals coming into a device from those it is sending out, acting as a kind of selective filter in between a device’s antenna and its radio circuitry. Circulators are already a crucial part of radar systems, but until now they have always been built using strong magnets made from rare earth metals, making them bulky and unsuited to the circuit boards inside devices such as laptops and smartphones.

The new circuit design avoids magnets, and uses only conventional circuit components. “It’s very cheap, compact, and light,” says Andrea Alù, the associate professor who led the work. “It’s ideal for a cell phone.”
Carla Gentry CSPO's insight:

This is definitely a significant research development,” says Philip Levis, an associate professor at Stanford. “It’s a very new way to look at a very old problem, and has some very good results.” However Levis notes that work remains to be done to convert the lab-bench breakthrough into something practical for the crucial frequency bands used for Wi-Fi, cellular, and other communications.

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13 New Trends in Big Data and Data Science

13 New Trends in Big Data and Data Science | Data Nerd's Corner | Scoop.it
Based on requests from clients - vendors of data processing platforms and products - as well as trends in popular blogs,  job postings, and my own reading. Her…

Via John Lasschuit ®™
Carla Gentry CSPO's insight:
The rise of data plumbing, to make big data run smoothly, safely, reliably, and fast through all "data pipes" (Internet, Intranet, in-memory, local servers, cloud, Hadoop clusters etc.), optimizing redundancy, load balance, data caching, data storage, data compression, signal extraction, data summarization and more. We bought the domain name DataPlumbing.com last week.
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John Lasschuit ®™'s curator insight, November 20, 1:47 PM

13 trends in #Bigdata an #DataScience. By Vincent Granville.

Russell R. Roberts, Jr.'s curator insight, November 22, 2:23 AM

Author Vincent Granville identifies 13 trends in Big Data and Data Science that will transform how businesses are run and managed.  Among my favorites:  The rise of data plumbing and the data plumber; the use of data science in unusual fields; increased awareness of security and data protection; the rise of mobile data exploitation; high performance computing; forecasting space weather; and digital diagnosis and treatment by robots.  These trends are already showing up in the market place.  Are we prepared to deal with this transformation in our business and personal life?  Aloha, Russ.

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Real-Time Revenue and Big Data | SmartData Collective

Real-Time Revenue and Big Data | SmartData Collective | Data Nerd's Corner | Scoop.it
Big Data Pitfalls
For those ready to dive into a Big Data implementation, be sure to weigh the pros and cons. According to a recent report by research firm Frost & Sullivan, three of the most common problems in big data deployments are incomplete data collection, false starts, and disruptive drains on IT and data-professional staff productivity.
Carla Gentry CSPO's insight:

The report goes on to say that the associated risks and costs of Big Data projects can be so draining that organizations new to Big Data projects should seek out assistance from technology providers or consultants.

 

The bottom line is that many organizations are not prepared, or do not have the resources, to take on a huge Big Data project.

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World supply chains under most threat from economic risk | News | Euro Supply Chain Jobs - Euro Supply Chain Jobs

Carla Gentry CSPO's insight:

Risk Index has found that while supply chain risk in the Middle East and sub-Saharan Africa has increased, neither the Ebola outbreak nor the advance of the Islamic State has led to a significant increase in international supply chain risk.

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Big Data Problem: Could Fake Reviews Kill Amazon?

Big Data Problem: Could Fake Reviews Kill Amazon? | Data Nerd's Corner | Scoop.it
Amazon authors are vulnerable to the following fraud, that would eventually result in significant business loss for Amazon.
A start-up company selling good reviews for $500 per book with a $100 monthly fee. It would work as follows.
A new book receives several negative reviews (1-star) using the methodology developed in the previous section
The author is then reached by email: typically, most authors have a public email address easy to harvest with automated tools, or easy to purchase from mailing list re-sellers
The start-up offers to post good reviews only (and it does not discuss the bad reviews previously planted before reaching out to the author to "fix" the problem)
Carla Gentry CSPO's insight:

How scalable is this? A college student could easily make $500 a day, targeting only a few books each day. That's $100k per year, and collect the money via Paypal. Because the money is relatively easy to make, a large number of (educated and under-employed) people could be interested in setting up such a scheme, eventually targeting thousands of authors each day when combined together. Or someone might find a way to automate this activity, maybe using a Botnet, and make millions of dollars each year. Many authors would eventually refuse to have their books listed on Amazon, and choose to self-publish with platforms such as Lulu. Publishers would also opt out of Amazon. Revenue on Amazon (from book sales) would drop. Or Amazon could simply eliminate all reviews and not accept new ones.

Interestingly, it appears that Yelp might be making money with a similar scheme: out of fake reviews and blackmailing small businesses listed on its website. And I've seen companies selling fake Twitter followers or Facebook profiles, though they quickly disappear. Even LinkedIn was recently victim of a massive scheme involving fake profiles automatically generated. 

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'Vegas' explores mining of our personal data : Ct

'Vegas' explores mining of our personal data : Ct | Data Nerd's Corner | Scoop.it
Gary Loveman, CEO of Caesars Entertainment, seems like an unlikely mastermind for a Vegas casino. After earning a Ph.D. in economics from the Massachusetts Institute of Technology, Loveman got a job teaching at Harvard Business School.

His research into consumer behavior led to the theory that the lifetime value of a single customer is affected by their satisfaction — the more satisfied a customer is, the more valuable they are to a company. When Loveman started to apply his research to casinos, he discovered that customers didn't show much loyalty to any single casino over time. He suggested that the best way to retain customers was to use data the company was already collecting to develop a more robust loyalty program.
Carla Gentry CSPO's insight:

In addition to data collected by casinos, Las Vegas is a trove of public data — more couples marry there than anywhere else in the United States. And the subsequent divorce records provide even more personal details that then become part of the public record, Tanner notes.

 

While U.S. law does restrict trade of some personal information like medical and financial data and how some types of data can be used for decisions like hiring or granting loans, the rules are otherwise rather thin.

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Understanding the Real Problem - Enterprise Complaints Analytics

Understanding the Real Problem - Enterprise Complaints Analytics | Data Nerd's Corner | Scoop.it
A couple of weeks ago, my team was asked to come up with a solution for an Enterprise Complaints Platform with Advanced Analytics capability for a Fortune 50 Bank. The initial scope statements were high level requirements like for example, Identification of high risk complaints that were likely to be escalated to regulatory agencies, Complaint Root Cause Analysis, etc.
It quickly became apparent that while the solution did include Advanced Analytics components what was really needed was a repeatable process for Data Discovery and Descriptive Modeling that would provide the Associates with a semi automated way to complete the Root Cause Analysis or provide a way to identify the initial set of categories that could be used as inputs for Advanced Predictive and Prescriptive Analytics.
Carla Gentry CSPO's insight:

With these challenges in mind, it became apparent that any proposal we made for an Advanced Analytics solution would require considerable pre-processing capability on the input data including Big Data and a workflow capability to provide the “value add” repeatable automated processes that the front line associates were looking for. While this may seem obvious in hindsight, it was a concept that was not immediately apparent when we started the evaluation with the business looking for a One stop solution to meet their Advanced Analytics needs.

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Selection of 29 external resources and articles from thought leaders - November 17

Selection of 29 external resources and articles from thought leaders - November 17 | Data Nerd's Corner | Scoop.it

An estimate that is slightly biased but robust, model independent, easy to compute, and easy to interpret, is better than one that is a non-biased, difficult to compute, mysterious, or not robust. That's one of the differences between data science and statistics. Also, many times, reinventing the wheel can be more efficient than researching the literature for days, to perhaps find and old solution, barely documented, that won't work any better than your (quickly designed) reinvented algorithm, on real data.

Carla Gentry CSPO's insight:

Starred articles were potential candidates for our picture of the week published in our weekly digest. Enjoy our new selection of articles and resources (R, data science, Python, machine learning etc.) Comments are from Vincent Granville.

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Amazon and 100-Percent Renewable Energy: Will It Really Happen? - Supply Chain 24/7

Amazon and 100-Percent Renewable Energy: Will It Really Happen? - Supply Chain 24/7 | Data Nerd's Corner | Scoop.it
With one quiet web update this week, Amazon becomes the latest tech giant with a less-than-stellar sustainability track record to hail a major potential shift in strategy.

Just a few months after the company hired its first corporate sustainability chief, Amazon cloud computing division Amazon Web Services has declared “a long-term commitment to achieve 100-percent renewable energy usage for our global infrastructure footprint.”

An Amazon spokesperson declined to elaborate on when and how the company might go about building out a clean energy portfolio, referring all questions about the company’s sustainability strategy to a corporate web page.
Carla Gentry CSPO's insight:

Still, shifting Amazon Web Services’ massive network of data centers serving corporate clients like Airbnb and Unilever to renewable energy would in and of itself be a noteworthy change

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Why data lakes don’t always need to belong to data scientists | Information Age

Why data lakes don’t always need to belong to data scientists  | Information Age | Data Nerd's Corner | Scoop.it
Qualified data scientists can strategically analyse disparate data sets, but other business users can tap that data too. While this can provide advantages, there are also risks.
Carla Gentry CSPO's insight:

If people apply incorrect methodologies to aggregated data, they can reach the wrong conclusions and base important decisions on false information, or even corrupt sensitive data. 

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Your Credit Score and Your Health - Consumer Reports

Your Credit Score and Your Health - Consumer Reports | Data Nerd's Corner | Scoop.it
The other problem with examining credit scores for psychological traits is that the scores are not perfect. While credit scores may be calculated differently in New Zealand, where the study was done, in the U.S., one in five consumers—about 40 million people— find errors in their credit reports, according to the Federal Trade Commission. Besides that, the exact algorithms for calculating credit scores are secret, making it hard for consumers to know how to influence the score they receive. Some consumers complain that they get dinged for confusing reasons such as making credit inquires.

If that's not enough to question the integrity of the credit score, a recent study from the Consumer Financial Protection Bureau shows that credit-scoring models may not accurately judge the creditworthiness of consumers. On top of that, consumers who have been victims of identity theft may also find their credit scores damaged. 
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Making the Internet of Things a business reality | Information Age

Making the Internet of Things a business reality | Information Age | Data Nerd's Corner | Scoop.it
Take the hypothetical example of a company that makes industrial printers. Through IoT-enabling their printers, that organisation can remotely monitor ink levels. This not only allows it to suggest to the customer that they need to buy more ink when running low, but also provides the capability to run diagnostics to see if the printer could be improved or needs repair, or up-sell to the customer a more efficient printer more suited to their task.
Carla Gentry CSPO's insight:

Connecting is more than just about linking devices to the internet. To achieve real business value, devices should be interconnected with a range of software and hardware to allow collected data to be collated and managed on key business systems. The connections created need to be adaptable to how the business wants to manage its devices and the information from it. Therefore it is vital to have an agile infrastructure that provides quick, simple and secure connections that are scalable - See more at: http://www.information-age.com/technology/mobile-and-networking/123458674/making-internet-things-business-reality#sthash.PDaRvDv7.dpuf

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DataFox Brings Private Company Analysis And One-Pagers To Mobile - TechCrunch

DataFox Brings Private Company Analysis And One-Pagers To Mobile - TechCrunch | Data Nerd's Corner | Scoop.it
DataFox, the online research platform that allows anyone to track information about private tech companies, has now brought its service to mobile in the form..
Carla Gentry CSPO's insight:

“One thing I’ve been happily surprised to see is that every large company in America has a team who are focused on the Valley, and the high-growth tech companies coming out the Valley,” says Janmaat. “The innovation is occurring at such a high speed, it’s really hard for these people who don’t have an office on Sand Hill Road or in SoMa to keep tabs on the companies that are up-and-coming, to prospect for interesting businesses, or to do research on them.”

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Using Data for Better Social Retargeting

Using Data for Better Social Retargeting | Data Nerd's Corner | Scoop.it
Retargeting on social media is quickly becoming common practice. Using data wisely may be the key to navigating the line between creepy and effective.
Carla Gentry CSPO's insight:

Creepy though it may be, it won’t be changing anytime soon. In fact, it’s probably going to happen more frequently. This is just another example of marketing’s changing landscape. Big data has taught us to learn a lot from the vast amounts of information produced everyday. Retailers can learn shopping habits from transaction records. Healthcare industries can be more reactive by anticipating outbreaks before they happen. There’s no limit to what businesses in any industry can learn. And while information can be gathered from almost anywhere, there is one medium that has drastically changed how we gain information more than the others

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Big data: managing the legal and regulatory risks | Information Age

Big data: managing the legal and regulatory risks | Information Age | Data Nerd's Corner | Scoop.it
Too many organisations enter into the hype of big data without a comprehensive view of the legal and regulatory minefield they're about to navigate
Carla Gentry CSPO's insight:

Too many organisations enter into the hype of big data without a comprehensive view of the legal and regulatory minefield they're about to navigate - See more at: http://www.information-age.com/it-management/risk-and-compliance/123458663/big-data-managing-legal-and-regulatory-risks#sthash.n7ieMZpr.dpuf

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I spent a weekend on a cruise ship staffed by robot bartenders

The two robots are perfectly efficient, fast bartenders. They always select the perfect amounts of Bulleit borboun, ice, and lime, and shake it just so before dumping it carefully into my plastic...
Carla Gentry CSPO's insight:

Quantum of the Seas is full of things like the Bionic Bar. Things that Royal Caribbean did not because it had to, or because it saved or made lots of money (though the company certainly hopes to do plenty of both), but because it could. Because those things just seemed better, and because Quantum of the Seas is meant to be what the company calls "a before-and-after" ship. This is supposed to be the first of a new kind of ship, the one that resets the bar for everything that comes after it. With it, Royal Caribbean seeks a different kind of cruiser, a person who would never before have considered spending their week-long vacation on a boat.

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Popular Software Skills in Data Science Job postings.

Popular Software Skills in Data Science Job postings. | Data Nerd's Corner | Scoop.it
This exercise was done to understand the software skills that are in high demand for Data Science. Analysis was done by extracting the job postings from popular online websites. The findings are interesting. R continues to be the most popular skill, found in 70% of the postings. Python follows as a close second. Surprisingly, in spite all the talk about "Big Data Science", SQL comes up third. This shows that traditional RDBMS still continue to be the base for machine learning work today.
Carla Gentry CSPO's insight:

The following chart gives the relative importance of skills. A frequency of 0.5 means the skill is found in 50% of the postings.

 

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What is Anomalous Behavior Detection? | Blog post

What is Anomalous Behavior Detection? | Blog post | Data Nerd's Corner | Scoop.it
Data lakes allow us to ingest not just classic security controls but wider data sets – HR, instant messaging, even video. Machine learning helps us learn the “allowed and normal behaviour”, from multiple users.  It identifies what is not “normal” by creating a scope of the deviation from the norm.
Carla Gentry CSPO's insight:
Detect social engineering attacks as well as network level detections – for example the external attack by someone calling random numbers at a company, claiming to be calling from technical support. The attacker will "help" solve the problem and, in the process, give the attacker access or deploy malware.
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The intersection of data and design is equal parts art and science - O'Reilly Radar

The intersection of data and design is equal parts art and science - O'Reilly Radar | Data Nerd's Corner | Scoop.it
One thing is certain: businesses can’t do LinkedIn-level data-driven decision-making on a shoe-string budget. As we’ll see later on in this chapter, real data-driven decision-making isn’t even possible at certain stages in the development of a company. Early-stage companies have, in most cases, far more pressing issues than split testing the color of a button.
Carla Gentry CSPO's insight:

One of the best descriptions that we’ve ever seen on the difference between data-driven and data-informed comes by way of Andrew Chen. In a post entitled “Know the difference between data-informed and data-driven,” he explains that “the difference…in my mind, is that you weigh the data as one piece of a messy problem you’re solving with thousands of constantly changing variables. While data is concrete, it is often systematically biased. It’s also not [always] the right tool, because not everything is an optimization problem. And delegating your decision-making to only what you can measure right now often de-prioritizes more important macro aspects of the problem.”

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“Carpe Datem”: Seizing the Opportunities of Big Data to Drive Insight

“Carpe Datem”: Seizing the Opportunities of Big Data to Drive Insight | Data Nerd's Corner | Scoop.it
Value-added content sources curated by subject matter experts in a consistent, controlled fashion are one antidote to help overcome the challenges of big data to capture its opportunity. These sources enhance the original content to highlight the most important and novel components in a uniform way, allowing for more complete search retrieval and precision.
Carla Gentry CSPO's insight:

Yes, big data is intriguing for its possibilities; but the ability to rapidly find precise answers, is also critical. Value-added content leads researchers more quickly to precise results, driving scientific insights and speeding review to find relevant answers. In the world of chemical discovery, researchers need to find answers from simple questions to the seemingly impossible. For instance, in pharmaceutical development, advanced search technologies with access to massive secondary databases enable scientists to quickly determine what has worked before, and what hasn’t; to view other previously investigated therapeutic indications for a new drug lead; to learn what protein targets may be implicated and to uncover possible side effects.

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Are TV Audiences Really on the Decline?

Are TV Audiences Really on the Decline? | Data Nerd's Corner | Scoop.it
Of note, the analysis does not look at demographic trends: the Nielsen data tracked on a quarterly basis by MarketingCharts does find that there has been a decline in traditional TV viewing time among youth, which has been offset by an increase among older viewers. (Interestingly, though, a new MarketingCharts report on the demographics of US media audiences finds that despite the talk of a graying broadcast audience, it’s actually the cable audience that’s graying more quickly. And as with various other media, affluent audiences over-index in their weekly viewership of broadcast and cable TV.)
Carla Gentry CSPO's insight:

It’s also worth noting that this analysis is limited to Q3 viewing, which might represent an anomaly from full-year trends. And at this point, it’s worth including in the discussion a new Flurry reportthat proclaims time spent with mobile apps has surpassed time spent with TV. While there’s no doubt that time spent with mobile is increasingly rapidly, the TV consumption figures used for comparison are from the Bureau of Labor Statistics, which have a daily average (of less than 3 hours in Q3) far smaller than the daily average reported by Nielsen (which is closer to 5 hours). So the comparison is still inconclusive, for now.

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