The planetary economy now spins on an axis of big data. Each of us feels pressure to evolve our skills in order to stay ahead of the big data curve. We do this both to remain employable and to seize new opportunities for professional and personal growth.
Organizations realize that they too must cultivate new skills in order to harness big data's never-ending gushers of fresh intelligence. Which new skills are essential? This past Thursday, June 7, 11am-12noon (eastern), IBM hosted a tweetchat on this topic, under the hashtags #IBMDataChat, #SmarterAnalytics, #BigData, and #Skills.
The event showcased how visionary organizations are recruiting, training, and growing their skillsets in the big data era. The chat was moderated by yours truly (@jameskobielus).
Primary participants were several experts from academia and the business world. We had many other participants from across the Twittersphere. What follows are the most noteworthy discussions.
Big Data Skills Are Key for the "Plugged-In Manager"
Griffith underlined the critical importance of big data skills for anybody hoping to establish themselves in the new economy: "As I tell my students: All
#job calls I'm getting are about #bigdata....[we] push faculty to make the [Big Data] connections in case [studies]."
Another aspect of Griffith's work is to help executives build, manage, and improve their organizations. She discusses this research in her new book, "The Plugged-In Manager" (http://bit.ly/Jvq6Aj), which stresses that you can't manage through people, technology, or organizational process alone. In Twitter compressed style (across several tweets), she discussed the requisite data analytics skillset of such a manager: " Use all resources ppl, tech, org ... Mix (no silo) ppl, tech, org.... Means need basic understanding x org."
She noted that higher education has not fully harnessed big data for its own competitive or operational advantage. "Operationally - we could [leverage big data to] learn about [the] learning [process]."
Data Science Coming into Business Decision-Making Processes
Manish Parashar is the Director of Rutgers Discovery Informatics Institute (@RDI2BigData). He is a professor in the Rutgers School of Engineering's Department of Electrical and Computer Engineering, director of the NSF Cloud and Autonomic Computing (CAC) Center at Rutgers, director of the Applied Software Systems Laboratory at Rutgers, and associate director of the Rutgers Center for Information Assurance.
Over several tweets, Parashar discussed the key business imperative in the big data era: "Your economic advantage depends on the data you have plus your ability to transform that data into meaningful insights..... Industries nimble enough to interpret & use the data in new ways to add value are the leaders.... The goal is use of data to revolutionize science and engineering and its impact on society.....We need to move away from our fixation on data size. Data quality & our ability to analyze it are more important."
The bottom line, Parashar tweeted, is that "Traditional decision-making structures must be adapted to incorporate data scientists in business and research." To that end, "Rutgers’ new MS in data science and discovery informatics injects big data into business decision-making.....Students not only need to learn tools to handle big data- they must learn how to integrate big data into their reasoning."
Statistics and Computer Science are Key Disciplines for Big Data Workers
Anders Rhod Gregersen (@andersrhod) is Data Scientist at Vestas Wind Systems A/S, which is a world leader in wind turbines. He is a specialist in high performance and data heavy computing. He designed and operates Vestas' Firestorm supercomputer, the third largest commercially used supercomputer in the world at the time of installation.
Gregersen tweeted that " Many of my power users are statisticians - they have a natural talent for data.... Data workers also need an understanding of computer science." Their core job is to "turn BigData into BigKnowledge, for that reason biz understanding is essential."
Being able to find the "needle" of golden intelligence in the big data "haystack" is a core skill for data scientists, Gregersen tweeted:
At Vestas we want to know all about the planet's atmosphere, including how the weather has been in your backyard past 12 years
That ends up being lots of data :-)
By knowing how the weather has been for the past 12 years we support our customers in maximizing their business case certainty
Normally such support requires met-towers and years of study - we now do it in minutes
So BigData has completely changed the way windturbines are sited at Vestas
But we also use BigData to "research" our planet's atmosphere, by identifying phenomenons - now just write a proper query
The extreme events are among the data "gold nuggets" we want to discover - knowledge of these saves us money
Data Scientist Skills in Hot Demand in Today's Economy
Stephen Brodsky (@BrodskyStephen) is IBM Distinguished Engineer, Big Data and Innovation Initiatives. Brodsky specializes in innovation and big data. His research and projects focus on technology change and entrepreneurial initiatives. Currently, he is looking at the capturing, management, and analysis of information for strategic decision making.
Brodsky noted that data science skills are in hot demand today:
The data scientist is the 21st century Sherlock Holmes!
In the future, we may have Data Science as a college degree.
Quantitative decision making will increasingly be based on Data Science.
Economies with more Sherlock Holmes/Data Scientists will have significant competitive advantage
With a mix of domain expertise and analytics skills you can turn data into the right insights.
Analytical skills will be important - data analysis as well as data structures in comp science study.
Probability and Statistics as well as Machine Learning will be great core skills.
Skills Gap in Today's Big Data Economy
Many other tweeters joined in the chat with interesting insights relevant to the skills gap in today's big data economy.
Shelly Lucas (@pisarose) of Dun & Bradstreet said: "Definite skills gap in
#BigData, per @IBM, ideal data scientists need stat & biz background....US shortage of 1.5 million mgrs/analysts w/skills u/stand & make decisions bsd on data McKinsey.
Henry Morris of IDC (@hmorrisidc) said higher education is addressing this gap: " I've visited Yale center, need 2 train future biz leaders on how 2 work w/ data scientists in modeling process."
Tony Baer of Ovum Research (@TonyBaer) says several trends will close the skills gap over the course of time: "No silverbullet. Smart creative people&better tools. Just as visualization made data mining tangible....Just as Gen Y has become computer-literate, tomw's bus leaders will become data-literate...It's very much a new twist on adv analytics& data mining that calls for expanded skills & creativity."
Continue the discussion & check out these resources
Here's an interesting recent article from the Wall Street Journal discussing how IBM and Rutgers are teaming to help New Jersey using Big Data to spur economic competitiveness: http://on.wsj.com/LsXO95
If you'd like to see how IBM and Yale and preparing the business leaders of tomorrow for the Big Data economy, check out this video: http://bit.ly/lQIgqz
Last but not least, here's a link to all Tumblr posts on IBM Smarter Planet analytics: http://bit.ly/hWdh
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