Another interesting perspective of value of big data in Big Data Gets the Algorithms Right but the People Wrong

To begin with, Big Data delivers thin data. In the social sciences, we distinguish between two types of human behavior data. The first—thin data—is from digital traces: He wears a size 8, has blue eyes, and drinks pinot noir. The second—rich data—delivers an understanding of how people actually experience the world: He could smell the grass after the rain, he looked at her in that special way, the new running shoes made him look faster.

A thoughtful and intriguing comment on the value of streaming analytics by an IBM’er in IBM’s Take on Big Data and How Hadoop Is Changing Integration

“It’s no longer enough to know what question to ask. Sometimes, it matters when you ask a question”

“In a big data world, sometimes the best thing to do is persist your question and have the data run through that question continuously rather than finding a better place to persist the data”

Hilarious quote in Don’t Stuff your Big Data in a Woman’s Handbag

“Using analytics to understand and exploit data will continue to increase in importance – but it’s clear from this report that organisations lack the process and infrastructure to make this a reality. Company data today is like a woman’s handbag. It may hold a lot, but actually finding anything in it is practically impossible.”

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We need big data analytics to shine the light  into the handbag.

A note on social media monitoring/analytics tools and its value from Big Data jumps to the cloud

“With a lot of these tools, you only have a 50-50 chance of getting the sentiment right,” TDWI’s Halper says. “It also depends on who you’re going with – if you pay peanuts, you get monkeys.”

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Same chance as tossing a coin and getting a head.    Why is it that social media monitoring, listening, and management still getting a lot of buzz within the unstructured world of big data?

A thoughtful HBR blog post How Google Flu Trends Is Getting to the Bottom of Messy Data, emphasizes the importance of both man and machine in enabling better decisions.

The Google approach suggests a certain data vigilantism comprised of smart people wielding smart algorithms to act as sentinels against faulty inference. Big data vigilantism can help your company cope with two of big data’s main issues: messiness and sampling bias, and ultimately help contribute to growing your confidence in wielding big data in your decision process. 

A nice note in a big push to big data usage.

A quote in Why creativity wins out over big data:

“It’s not just a question of surrendering creativity to data, it’s the danger that if you just measure in the short term, which is what big data makes you do, it turns you off all the things driving success in the long term,” Field claimed.

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Can’t creativity (“big idea”), data of all types (small, medium, large, extra large), technology, and human intelligence (plus the ability to translate the big idea into actions with data and tools) coexist and lead us on the path towards both short-term and long-term business success?  The optimal mix of the ingredients will vary over space and time, and across functions within an organization, but undoubtedly both left and right halves of our brains matter.

The quote below in Big Data Hasn’t Changed Everything reminded me of Splunk’s Hunk tool (point the tool at the computer cluster and then magic happens).

Managers are constantly being told that they are one hardware or software installation away from business nirvana. But they should bear in mind the lessons of the financial crisis the next time a consultant waltzes into their office declaring big data the next big thing, or even worse, a “paradigm shift.”

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Big data continues to garner bad press.  It is high time there are successful use cases outside the usual suspects – Google, Facebook, Netfix, Amazon, Twitter and exceptions such as Wellpoint Healthcare and Progressive Insurance.   Data – small, medium or big – is not the entire wheel, but just another spoke in the wheel.

An interesting perspective on big data and Hadoop from a Microsoft VP in Microsoft: Hadoop ‘Cornerstone’ Of Big Data’s Future

“Microsoft is here [Hadoop Summit 2013] because we’re in this partnership with Hortonworks, with the community, deeply involved to help get Hadoop out, literally, to a billion users,” Clark said.

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This is the real democratization of “big data”, i.e., big data for the masses.

About 5 years back, cloud computing was the best thing since sliced bread. Numerous books were written about what it is and how it will revolutionize everything. Really?
Move ahead few years, and we have a new kid on the block (or a shiny toy) called “big data”. Few books are already out on big data and how our lives would change forever. Maybe?
The search trends for “cloud computing” and “big data” indicate how cloud computing has lost is lustre, and “big data” is taking up the mindshare of boardrooms and data scientists alike.
Maybe there is a simple lesson for peddlers of the next IT revolution. Focus on talking less about what it is and what it can do, and more on creating measurable value for enterprises, i.e., positive impact on enterprises.
Maybe there is a more important lesson for buyers of “big data”. If your organization currently does not leverage existing data, ignore the IT peddlers, and instead focus on creating value from existing information assets – small, medium or big data. Once you have the organizational mindset, culture, and talent to act on insights and foresights from currently available data, even if they are in separate functional silos, then venture out into the world of “big data” in small steps.