Big data is too big for one title to tackle. Organizations need to build big data teams instead, according to experts
Much is being said these days about the perceived lack of data scientists to tackle the looming statistical and analytics demand over the expected growth in big data technology adoption.
However, two partners with professional services firm PricewaterhouseCoopers LLP believe that discussions around the talent crunch has to change its focus
While the PwC’s recent Digital IQ survey of more than 1,100 business and tech executives found that a mere 44 per cent of respondents believe there is enough talent to reap the benefits of big data, Anand Rao and Oliver Halter, partners at PwC’s advisory services, said organizations should be looking to hire candidates that possess different skills rather than concentrating on the narrow field covered by data science.
“Big data is too big for one title to tackle,” they said in a recent article on the online business and technology publication BaselineMag.com. “We need to build big data teams.”
The duo argues that a cohesive team from disparate departments could bring together multidisciplinary skills, experiences and techniques that would be ideal for deploying new applications that feature the collective insights of the organization.
There are five steps to build such a team and it all starts with breaking down the big data talent needs of the company.
Rao and Halter said there are typically four areas where firms need big data talent:
Business analysis – This is an area where knowledge about marketing, sales, distribution, operations, pricing and risk among other is needed. There is also a need for staff that can ask the right questions and articulate how information and insight can help identify the right course of action
Analytics expertise – This area deals with solid understanding of statistics and computational techniques.
Data technology expertise – The ability to understand external and internal data sources and how the gather, store and retrieve information is crucial in this area. The data technology expert has to be proficient in manipulating large data store and in using different tools to analyze data
Visualization expertise – The means to turn statistical and analytical data into graphs, charts, animations and other visual forms that are easily understood is vital in the process of drawing insight from big data. This expert will have a keen understanding of visual arts and design in order to generate reports and visual content that can be consumed in a variety of screens.
Once the organization has determined in talent needs, it can then proceed to the next four steps which involves:
- Evaluating the internal talent pool
- Filling your talent gap from other sources
- Cross-training to improve and enable your team
- Empower your team by giving them freedom
Stock exchange lowers latency and increases availability with HP
This case study provides an overview of why the National Stock Exchange turned to HP to meet specific needs for a next-generation server and storage infrastructure with high availability and ultra-low latency to support online transaction processing and data warehouse solutions.