What is big data?
Large enterprises are congregating electronic data from assorted sensors, and electronic devices, which are of different formats, with the use of independent or connected applications. This data inflow has outpaced the firm’s efficacy to process, analyze, store, correlate and understand the captured datasets. This new voluminous dataflow which doesn’t fit into the ambit of decorous data processing techniques has been nicknamed as big data. It has carved itself with a home in this dynamic and expanding information ecosystem that many companies struggle to manage today. Mckinsey Global institute ascribes “Big data” to datasets whose size is above the dexterity of archetypal database software tools to capture, store, manage, and analyze.
The concept of big data has chiseled itself to reality with appropriate hardware platforms and analytical tools in order to harvest business value through the new generation information platforms. The term “big data” has materialized itself as a magic wand transforming imperfect, complex, unstructured data into actionable information in the right hands with the right tools. Such transformations have been made possible with advanced computational tools and the new generation thinking. The transformed data divulges the trends and correlations within and across large dormant data sets that would otherwise remain undiscovered. The organizational roles responsible to ensure such data transformations are called as data scientist.
What is the talent identification challenge?
When organizations strategize to operate in the Bigdata space, it is cardinal to hire the scanty data scientists to drive their strategy. However the challenge faced by the hiring managers is to grasp the techniques of distinguishing big data talent, allure it to the enterprise, and make it productive. There is an astute shortage of data scientists apart from the fact that the differentiating factors on identifying the data scientist is also lacking from the view of the hiring manager. To add to the blues, there are no university programs offering degrees in data science to help the hiring managers. There is very little consensus on where the data scientist role fits in an organization, how data scientists can add the most value, and how their performance should be measured. There are several debates along these lines in the HR forums.
What is data science?
Consistently the term “Data Scientist” is being referred to in most of the job portals worldwide. This term exudes from the transpiring discipline of data science. Wikipedia outlines data science as a discipline incorporating aspects of mathematics and statistics, principles of pattern recognition, data engineering, advanced computational techniques, data modeling, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products. Harvard Business Review calls data science the sexiest job in the 21st century[1].
Who is a data scientist?
The new breed of “data specialist” christened as “Data scientist” has started dominating the field of Bigdata. It is vital to distinguish the role of data scientist for the purpose of clarity and better understanding. According to D.J.Patil, a data scientist data scientist is an embodiment of creativity, curiosity along with technical expertise.[2] When DJ Patil, chief scientist at LinkedIn (@dpatil), was interviewed on the attributes of a data scientist, he made it clear that he is looking for a person with whom he can start a company, since the current century is reliant on data products and the data scientist is expected to churn up new and novel data products. According to Rachel Schutt, a senior research scientist, Johnson Research Labs, data scientist is: “an amalgamation of a statistician, computer scientist and a software engineer who is curious, with excellent thinking capability.”[3]
As witnessed from the internet literature, the emerging role of data scientist has the dexterity to break larger problems into smaller problems. The role is usually interdisciplinary with heterogeneous skills. The role is conceived to have the ability to look at the bigger picture with clarity and is expected to have the innate talent to combine entrepreneurship with patience. The role functions with the freedom to experiment and explore the inflow of digital data cognate to the chosen industry. The role dazzles with a specialized quality of identifying data problems, explore the voluminous data sets, building and iterating over the possible solutions leading to incremental data products.
Data scientist have emerged as the successful breed of workforce who can understand how to pick out solutions to emerging business questions from the tidal wave of structured and unstructured information. They are virtuoso with the training and curiosity to generate new discoveries from within the world of big data. Data scientists envisage technical limitations as a part of their quest for solutions and do not allow that to extirpate their search for novel solutions. As they discover novel solutions they disseminate what they’ve learned and suggest its implications for new business directions.
What is the surge for Data scientist?
The demand for data scientists has been actuated by the ascendancy of the major Internet companies like Google, Yahoo, Amazon, Facebook, Linkedin etc. Some of the other companies in the look out include Aureus Analytics, Mumbai, Walt disney world, Orlando, Data scientist, Bangalore Big data developer, Capitalonelabs, NYC, Syrinx, Data scientist, Bank of America, Data scientist and Sr.Data Scientist, Bing, Neel Sys India Pvt Ltd, Visakhapatnam etc. The emerging Big data atmosphere has the aptitude to metamorphose the face of management theories lading the world to a different planes of management concepts. McKinsey Global Institute clearly points out in its report the fact that the United States is forced to increase the number of graduates with skills handling large amounts of data by as much as 60 percent. HTC ITMR has come up with a couple of interesting programs in Big data with a focus on Hadoop and Map Reduce. The gold rush has started ticking and various organizations have started fishing for talent in the dwindling pool of data scientist to accumulate gold.
Reference:
1. Thomas H. Davenport, D.J. Patil, The Sexiest Job of the 21st Century, Harvard Business Review October 20122. D.J.Patil, Building Data science teams, Oreilly, 2011
3. CLAIRE CAIN MILLER, http://www.nytimes.com/2013/04/14/education/edlife/ universities-offer-courses-in-a-hot-new-field-data-science.html? partner=rss&emc=rss&smid=tw-nytimes , Published: April 11, 2013
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