Sunday, May 6, 2012

Three Big “WHO”s to Master Big Data

Big Data is big deal & big distraction as we put in Three Big “WHY” for Big Data.  There are three challenges Big Data presents.: Ocean of data amassing with departmental silos; The second is the old “needle in the haystack” problem; The third is making use of the information by developing framework and methodology to find meaning in it..

At series of blogs, we also explored: Three Big “WHAT” about Big Data; and Three Big “HOW”to Tame Big Data, and now it’s time to be more specifically asking Big WHOs: who are those data masters and data stewards to form a successful dream team and conquer the Big Data challenges:

1. Big Data Visionary

As we addressed above, the first Big Data challenge is the fact that the mountains or oceans of data many companies are amassing often lurk in departmental “silos,” how to manage data life cycle including data storage, data cleansing, data integration, data integrity, data governance,  timely exploitation., etc. So who are these data visionaries:

  • Executives who sponsor Big Data: such as: CIO & CMO & like-minded executives understand business’s long term view, proactively craft Big Data strategy as a core element of strategy,  and sponsor on experiment with calculated budget and resources. 

  • Data Enthusiasts with intuition & vision: who can help recognize game-changing effects of big data; who can connect the dots to focus on the business issues, to add fresh insights, sharp perspectives and different capabilities, who know what questions to ask, and then be able to translate the answers into business strategy or operational effect

 2. Big Data Analytical/Technical Expert

To conquer the second challenge: the old “needle in the haystack” problem of uncovering the information you need amongst the massive amounts of data, is making use of the information by developing framework, talent and methodology to deploy,  you need have:

  • Data Scientist/technical expert who can build up a flexible infrastructure which can integrate information and scale up effectively to meet the surge, who can also understand and employ quantitative methods, design, test and deploy models,. experiments, algorithms, and analytics can make sense of all this information.

  • Analytics specialists: who can practically deal with data, who understands how to take data and can take on the basic manipulations of the data in databases and management tools; who can program and apply the statistical learning and modeling techniques used for extracting information from that data.

3. Big Data Solutionary

  The third Big Data challenge is to find meaning in it. Big Data is the means to the end, not the end. The key is to turn the data into understandable information analyzed and transformed into knowledge which then be abstracted as wisdom that allows people to make better & faster decisions. Technical driven analytic niche expert on team are important, as building data models, understanding them and running them is important, but pure technologist won’t get you too far, data solutionaries are those:

·        Emerging hybrid business-IT Analyst: who can make sense of the tsunami of data flowing through cross-silo corporate systems; who can also excel at blending IT and business together for great outcomes, to solve the complex business problems.

·        Data masters who can interpret data, who can use creativity to ask provocative questions, who can think “outside of box” about experiments to run, who can ponder questions such as,
1) How does information flow?
             2) What forces underlie those currents?
             3) What’s the best way to pull insights from that sea?
             4) And how does the way a company works influence what data is available and  
                who can find it?
            5) 80/20 Rule: every bit of data is fact, but not all data are created equal, how to
                 get the best value via the most critical 20% of data?
             6) How to improve business capabilities via the data insight?
             7) What are the set of KPIs to measure Big Data project?

 As Joke on the web: “The data scientist is the data analyst who lives in California”, it may uncover two pieces of truth: Data mining might be the new gold rush in 21st century; and data masters not only need hard discipline, the soft skill is even more critical to tame Big Data-a big learning effect to combine the science and art.

Through asking Big Whos, successful companies are likely to be the ones that cultivate their talent masters, and compete on insights—striving to derive insights that matter and applying them to their business.


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