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Big Data: Help Wanted: Need More Data Scientists
Both the hardware and software technologies are evolving at a rapid pace, increasingly making it possible to perform ‘Big Data’ analysis , but there is a fairly big gap in the number of trained technologists who are productively able use the available tools. A recent study sponsored by EMC investigated this gap. The report validates that a Big Data skills gap does exist, and the report also identifies which skills and qualifications are needed by data scientists to productively work in the area of ‘Big Data’.
Big Data can be used by companies to make better decisions and also for them to learn more about the needs and behavior of their customers. The EMC report found that very little is being done in this area by most organizations currently. The report found that in most companies, the use of business data for analysis is often off limits, either because of policy or, more likely, tools and interfaces to get to the data simply don’t exist.
Decision Making – Only one-third of companies mine data to make business decisions
Customer Insight – Only 38 percent of companies say they use data to help them better understand customers
Lack of Data Access – Only 12 percent of business intelligence analysts say that employees have access to data for analysis
The EMC report found that there is a severe data scientist talent shortage.
Talent Shortage – 65 percent of data science professionals predict a shortage of Big Data skills. 83 percent say that new technologies are increasing the need professionals in their field.
The report profiled the skills of a typical data scientist as follows:
- Strong skills in both business and technology
- Involved across the data lifecycle, including the filtering and organization of data as well as visualization and analysis of it
- More than three times as likely as business intelligence professionals in having a Master’s or Doctoral degree
- Love to use scripting languages like Python, Perl, BASH and AWK.
Andreas Weigend, Ph.D Stanford, Head of the Social Data Lab at Stanford and former Chief Scientist Amazon.com, said that “We live in a data-driven world. Increasingly, the efficient operation of organizations across sectors relies on the effective use of vast amounts of data. Making sense of big data is a combination of organizations having the tools, skills and more importantly, the mindset to see data as the new oil fueling a company. Unfortunately, the technology has evolved faster than the workforce skills to make sense of it and organizations across sectors must adapt to this new reality or perish.”
