Big Data Lean Talent
“I feel comfortable operating with incomplete data”
” My data files are often messy”
“I explore data to see what it tells me”
“My dataset is so big, managing it is a part of the challenge”
“My findings drive operational and strategic decisions”
Well, I am searching for one who says some of these, with some confidence. It has been a populous segment with razorthin hits!
EMC, in its recent research, called out these as the core skills for the Data scientists. In its survey, 83% of people felt that new technology would increase the demand for data scientists, and 64% believe that it will outpace the supply of available talent.
Read the detailed survey and research from EMC here.
Also read the ZD Net Article on the Talent gap in the Big Data Talent space. Look at the emerging big impact Big Data roles and which one you would like to step into, to contribute in this space of big data transformation:
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- Developers: Build the platform and analytics apps. “They have familiarity of the tools or algorithms, they might be writing or packaging or optimizing or deploying different MapReduce jobs. “They’ll source and maintain different libaries.”
- Data analysts/data scientists: These professionals apply algorithms to analytic problems, and do data mining. “Their ability to tell a story with the data is what defines them. They may have domain expertise. They’ll help create data products, create data solutions that drive the business.”
- Data stewards: Ultimately responsible for the collection of quality data “Data stewards curate and catalog all the incoming data. There’s a lot of data floating around organizations, and Hadoop can get it centralized. So identifying the upstream data models, having a background in ETL [extract, transform, load] and data modeling are all typical skillsets and backgrounds.”