How ‘Big Data’ Is Different

[…] According to an industry report prepared by McKinsey Global Institute, the effective use of Big Data is a key basis of competition and delivering a new wave of productive growth. In other words, managing, analysing, visualizing, and extracting useful information from large data sets will help organizations to increase operational efficiency, to inform strategic direction, to develop new products and services, to identify new customers and markets, to make better decisions and to become more innovative. (Davenport, Barth, & Bean, 2012). […]

[…] MIT Sloan Management Review , 2012 – How ‘Big Data’ is different […]

[…] https://dev03.mitsmr.io/article/how-big-data-is-different/ […]

@thomas @paul @randy, thanks for a great summary. I'm currently researching big data for transformation as that will be a channel in the Chief Digital Office [http://chiefdigitaloffice.com], and Enterprise Analytics is a source. [http://bit.ly/eadavaz]. Although implied in points 2 and 3, I'd like to put in that part of the "magic" in big data analytics is knowing what questions to ask, given the data that's practically available (constantly changing), business goals and users. I say this because my firm has a defined methodology for its Ecosystem Audit offering in which we create analytics for understanding social data and we go far beyond social media monitoring platforms' reports. As the architect of the methodology, I find it both analytical and creative to use the data to get the answer for the question whose answer you need. We focus on things like trust and how it changes based on interactions, and quantitatively. It can get quite messy, but it works consistently. Given this, I can imagine that traditional data analysts, who are presumably accustomed to structured environments, will have a harder time in the "chaos" of the accelerating, external web, whose data is undoubtedly growing faster than internal structured. You have to be creative with social data because you are measuring human behavior and making logical inferences; thankfully, you can test the models quickly and fairly easily. Thanks again for a great summary!

As a creative opportunist helping fast growth SMEs innovate from their existing intellectual assets, I find the above article fascinating.  It seems to me that the interpretation of the big data gives large companies access to their own speedy Boyd loops in a ways they will not previously have anticipated.

Enjoy the article and good comments above, my take is: Big Data brings opportunities, also some distractions, only the well-mixed analytical team can work seamlessly to solve Big Data Puzzle --The business insight in decision making, customer experience optimization and talent management: http://futureofcio.blogspot.com/2012/08/three-big-insights-from-big-data.html

Big Data also means the full data life cycle management, from data storage, to data governance, but still need keep in mind: Big Data is means to the end, not the end. thanks

A very thought provoking article. In my opinion application of these concepts have been incubating for some time. Success is in the execution. The need to differentiate data and how it is utilized (i.e. labels of scientist vs. analyst) seems unnecessary. Yes, Ph.D’s with an MBA who want to code may be in short supply, and in 3-5 years do you feel that will still be the ticket to the club? It sounds like an important skill that is hard to find is the ability to be a boundary spanner. Combine this with the ability to access disparate information, synthesize, and apply it to solve business problems in ways that were not available before. The strength of the big data buzz will be that information value is based in the business unit and not in IT. It’s the concepts of velocity and ubiquity of technology to enable access to the right information that makes big data a big topic to me.

What you describe is fundamentally the difference of data at rest in reports, poured over by data analysts and data in motion, managed by data scientists who are looking for trends, flows, processes. Those static reports built up knowledge, but data in motion IS knowledge.

Big Data is about patterns more than discreet elements of information and that's where everything changes. There's a pattern of intelligence that has always been elusive and much like the The Matrix where some people could watch the flow of green 0's and 1's to see what was happening in real-time. 

I wrote up this idea here: http://successfulworkplace.com/2012/07/23/data-in-motion-divides-the-haves-and-have-nots/

A great introduction to the new capabilities big data brings to the business! I need, however, a little clarification on what you think IT's role is or would be in the adoption of big data. You recommend "Moving analytics from IT into core business and operational functions." But you also say "IT organizations will train and recruit people with a new set of skills who can integrate these new analytic capabilities into their production environments."

Could not agree more with points 1 and 3.  In my article "The Big Bang of Marketing:  Big Data" http://intothecore.com I discuss briefly how the importance of any type of 'big data' initiative is to find the story/the trend journey behind the data that leads to meaningful consumer insights that drive long-term engagement if the right questions are known.  Data knowledge must be taken to the operations/marketing groups from IT in a partnership that is synergestic with the IT reporting role and the user role of functional/vertical groups.  
Finally, quants professionals should not be expected to be the sole interpreters of data, business and marketing knowledge is critical to get the 'big picture' of 'big data'.