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Beyond Marketing
Problematic, tools, news, in marketing and beyond to develop ecosystemic vision; are included Inbound Marketing, Content Marketing, Social Media...
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Strategic data vs. data theater in data-driven marketing

Strategic data vs. data theater in data-driven marketing | Beyond Marketing | Scoop.it

In a recent Teradata report, “lack of needed data” was cited as the least common obstacle to data driven-marketing. Only 22% of the marketers surveyed said that’s what held them back. The most common obstacle? “Lack of process to bring insights into decision-making.”

Denis Failly's insight:

"Good data helps us make choices in the definition or execution of a strategy.

Bad data, on the other hand is merely data that we show off for its own sake. It presents a facade of being analytical. There are dashboards and visualizations, infographics and reports, and plenty of pretty PowerPoint slides. But it lacks purpose. It may tell us if we hit our goals or missed them. But it doesn’t help us achieve them any better than saying, “Try harder!”"

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Big Content: The Unstructured Side of Big Data

Big Content: The Unstructured Side of Big Data | Beyond Marketing | Scoop.it
Denis Failly's insight:

Unstructured informations are predominant, underutilized, they are the new challenge : Big Content

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Gartner’s Big Data Definition Consists of Three Parts, Not to Be Confused with Three “V”s

Volume, velocity and variety characteristics of information assets are not three parts of Gartner’s definition of big data, it is part one, and oftentimes, misunderstood. Most people only retain about one-third of what they read —  that explains the truncation. However, to get to the essence of the definition, an effort to comprehend and retain more than what is limited to a single tweet is well-advised even in our fast-paced time. Especially given that Gartner’s big data definition is not much longer than a tweet:

Denis Failly's insight:

Precision around 3V in Big Data

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Big Data, Little Data: A Customer Experience Opportunity Waiting to Happen

Big Data, Little Data: A Customer Experience Opportunity Waiting to Happen | Beyond Marketing | Scoop.it

According to Wikipedia, Big Data is a collection of data so large and complex it becomes difficult to process…  However, many companies embrace a different concept of Big Data. While the collection of data is broad, based on a large amount of information and customer feedback, these companies are able to filter through it to understand general customer behavior and trends. 

Just this week RetailWire, a daily online publication, posed a question about Big Data versus Little Data.  A term not quite as well known, Little Data is a collection of information on an individual or smaller group of customers. 

Denis Failly's insight:

Big data gives you trends to make major decisions. Little Data gives you information to keep your best customers coming back.

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3 Creative Ways to Leverage “Big Data”

3 Creative Ways to Leverage “Big Data” | Beyond Marketing | Scoop.it

“The future is not big data, the future is big understanding, and it’s not the same thing.”

 

 

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Big Data: It Doesn’t Mean What You Think It Means

Big Data: It Doesn’t Mean What You Think It Means | Beyond Marketing | Scoop.it
Marketers must stop abusing the term Big Data in order to harness it. Here's how.
Denis Failly's insight:

Should we not to speak about "Great Small Data" or "Great Small and Smart Data" than Big Data

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Pundits: Stop Sounding Ignorant About Data

The current surge of enthusiasm around big data has produced a predictable backlash. Some of it, like Gary Marcus's New Yorker post "Steamrolled by Big Data,"is insightful and well-reasoned (even though I have my quibbles with some of his points). This is not surprising, since he's a neuroscientist as well as a writer, and so quite comfortable with data.

Unfortunately, some other prominent commentators clearly aren't. David Brooks has taken up big data in his New York Times column recently, and literary lion Leon Wieseltier posted last month in The New Republic about "What Big Data Will Never Explain." Now, these guys are entitled to write about what whatever they like, but if they want to be taken seriously when discussing data they really should stop the kinds of elementary mistakes they've been making so far. Their errors of understanding and fact weaken their credibility and turn off quantitatively adept readers.

So as a public service here's a short list, written for non-quant-jock pundits, of things to keep in mind always when writing about data and its uses.t

 

 

Denis Failly's insight:

That sound like a warning : Human vs Algorithm

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Data Not Included – The Era of the Data Steward

It’s all because of connectivity, don’t ya know?  The “Internet of Things” is a simple concept – anything can be connected to the Internet.  Anything.  An embedded electronic gizmo, smaller than a fingernail, and boom, there it is – in your browser or app – that “thing”, transmitting all sorts of information.  Trivial things, such as a reminder to water  flowers; and critical things, such as a jet engine signaling it’s statistically likely to fail on its next flight.  All this information, all this new type of data and the sophisticated analysis to make sense of it – is real. But, it will take many years to realize the revolutionary impact big data and big analytics will have on us.  Importantly; however, we have passed the point of no return – the big data and big analytics craze, in all its hype, evangelical praise, and emphatic disdain, is secular and irreversible.  Welcome to the “Era of Transformation”.

Denis Failly's insight:

The data steward does the strenuous lifting to prepare the data so it’s ready for the data scientist. The data steward will gather data from a set of these practically infinite data sources, collect them, format them, assure their quality, and then take these data sources and make each one seamlessly available to many data consumers.  It has to be repeatable, scalable, and done rapidly and often.  It likely needs to be self-service for the business user.  The steward will be required to provide internal, transactional, long-lived, short-term and real-time data.

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Stop Hyping Big Data and Start Paying Attention to 'Long Data'

Stop Hyping Big Data and Start Paying Attention to 'Long Data' | Beyond Marketing | Scoop.it
Our species can’t seem to escape big data. We have more data inputs, storage, and computing resources than ever, so Homo sapiens naturally does what it has always done when given new tools: it goes even bigger, higher, and bolder.
Denis Failly's insight:

"to really understand the big picture, we need to place a phenomenon in its longer, more historical context."

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