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Yes, Catch It Here and Hold It Down: Stuff On the Wind, In the Air About Data

The web is alive, overflowing with stories, blogs, facts, gossip and fragments of stuff about almost everything. One strand of it is data. There is lots of data about data. MBF Blogs sniffs the breeze to bring you some. It’s a new service we’re giving away here, and we’ll pick different themes and bring you some to you save time…

1. Data are not sexy

Kyle Reis of TechSoup Global blogs on Glass Pockets about data. Data are. Data is.

He goes on: ‘Personally, I love data. But we all know what invariably happens when the ‘D’ word comes up in conversation other than at a hackathon or Google staff party. Our eyes glaze over, we nod that, yes, this is indeed the era of Big Data, and then excuse ourselves to freshen our drink.’

He says that it’s not that he loves data per se but ‘what can come of data, particularly when it gets big and varied. Often, a surprising thing happens: the data get interesting. Really interesting. Even more importantly, the data become meaningful. Individual data points begin morphing into larger concepts like, say, The Law of Large Numbers….’

Interestingly, his blog appears on two other sites too, more or less word for word, PhilanTopic a blog of opinion and commentary from Philanthropy News Digest. And on the TechSoup forum.

So, it seems, not only are big data ‘sexy’, they are also ubiquitous. But we knew that anyway, didn’t we?

2. What’s the Story in Your Data?

This is a post on QSM by Katie Costantini which reviews a book, The Functional Art by Albert Cairo – which sets out to explain what data visualizations are, why it is significant to pair data and design, and how to assess whether a data visualization is “good” or not.

3. A Personal Analysis of Big Data

Matt DiBona, Director of Enterprise Management, blogs at Smartbridge about clearing out his email inbox: I was struck by the sheer volume of email marketing I receive containing the term ‘Big Data’. While volume is one of the proverbial 3 V’s of Big Data (more on this in a minute), I don’t believe they were referring specifically to the Big Data-related contents of my inbox. That said, email is certainly a target for Big Data analysis, but I’m getting ahead of myself.

‘In the interest of extracting some value out of the otherwise mundane chore of cleaning out my inbox, I’ll use this as a chance to share the key points I’ve gleaned from this pile of email marketing, tempered with my personal experiences, and infused with the perspective of other industry experts. Consider this my definition of Big Data….’

He then goes on to write about the 3 Vs – volume, velocity and variety. Worth a read if you like definitions. And if you like all his other Vs as well – veracity, variability, visibility, verification and value.

4. Email Marketing Data

Continuing on email marketing, Kara Trivunovic writes on Email Insider about data and marketing: ‘Recently, I was chatting with a brand marketer about data she might use to execute lifecycle marketing programs. Some of the data points were basic, like date of last purchase and date of last engagement. But there were other ones, including product last purchased and category of last purchase which, without the right context, could really throw a monkey wrench in her targeting, segmentation, and content strategy approaches.’

Why? Because data, especially when monitored during a confined timeframe and without context, often doesn’t provide enough information to tell the full story marketers need to achieve their objectives.

She goes on to explain that simple data like what a customer purchased will not tell the whole story. A one-off purchase in a certain category may be just that. You need the bigger picture (data) to predict future purchases.

5. A Very Short History of Data

For those interested in knowing about and contributing to the history of how data is used as it is, A Very Short History is ‘in the process of researching the origin and evolution of data science as a discipline and a profession. Here are the milestones that I have picked up so far, tracking the evolution of the term “data science,” attempts to define it, and some related developments.  I would greatly appreciate any pointers to additional key milestones (events, publications, etc).’

Linked with that, the history of how big data got to be big is discussing attempts to quantify the growth rate in the volume of data or what has popularly been known as the ‘information explosion’ (a term first used in 1941, according to the Oxford English Dictionary).

6. High-Performance Analytics

Alison Bolen writes a blog on SAS Voices that what we all ‘know instinctively is that many stories are better told in images’ and images should be an essential part of a technology strategy for big data analytics.

She says that big data ‘streams in so quickly and in so many formats that the first challenge is sorting it out to begin with. It is recommended that a process to stream, score and store that involves applying a level of analytics at the start to determine is established whether each piece of data is valuable enough to keep. Once your data is sorted in this manner, you can get to work analyzing it for competitive advantage.’

7. More data and opinion to digest:

Big Data Is Worth More Than Gold and Oil Put Together, 3 September 2013

No Place for the Human Touch in Complex Algorithms, 20 August 2013

If More Data Sharing Is the Answer, What is the Question? 29 April 2013

Image: SAS Voices