Modern enterprises have an immense responsibility to harness ever-evolving data technologies to get maximum business benefits. However, with new technological capabilities promising more value-added outcomes, global organizations face a challenge to recruit the most qualified Data Scientists and Data Analysts who can do justice to such promising technologies as Big Data, Hadoop or Predictive Analytics. Thus, while it is evident that businesses must continue to invest more in data technologies and tools, they must also provide the right kind of Data Science education and training to aspiring data professionals in order to successfully meet the business challenges of tomorrow.
The following resources serve as clear evidence of this business imperative:
Gartner’s 2016 Magic Quadrant for Advanced Analytics Platforms identifies IBM, SAS, KNIME, and Rapid Miner as a few of the industry leaders who are the most likely candidates for guiding future market visions. Gartner suggests that each and every organization should include at least two of these leaders in their evaluation shortlist of typically five to eight vendors. Many of these organizations also place education as top priorities for their employees.
MGI Proclaims Big Data to be the Next Frontier for Innovation and Competition
McKinsey’s global research arm, The McKinsey Global Institute (MGI) has provided extensive research-backed data in its report titled Big data: The next frontier for innovation, competition, and productivity,to prove that growing transactional databases, mobile commerce, multimedia content, popularity of social media, and sensor-aided gadgets all contribute to the exponential rise and accumulation of data in our everyday lives.As this trend continues, McKinsey warns that sophisticated Big Data technologies and able Big Data professionals will be needed soon to make sense of this torrential data flow and extract business value out of it.
A recent Economic Times article reported that Data Scientists and Data Engineers were in high demand throughout 2015. Many organizations of various sizes have been frantically reaching out to Data Science boot camps and fellowship programs to recruit qualified professionals.
The above cited evidence demonstrates that in this increasingly data-driven business world, Data Science and Analytics are necessary opportunities waiting to be seized and utilized for complete transformation of business operations. However, Data Analytics cannot be captured within a set of technical skills; a skilled Analyst will have to be an expert in probing and uncovering business problems as well. The professional Data Scientists and Data Analysts must possess a combined wisdom of mathematical and statistical abilities, sophisticated problem-solving capabilities, and business insights.
The collective goal of education and training in Data Science and Analytics is to prepare the next generation of Data Scientists and Engineers for the new global data economy.
Data Science Educational Opportunities May not be There Yet
Jennifer Lewis Priestley, the creator of Kennesaw State University’s (KSU’s) Ph.D program in Data Science, candidly admitted during an SAS Analytics conference that most Data Scientists today do not have the depth or breadth of analytical skills required for the coming decades. The implication of such an observation is that the current postgraduate-level academic programs in Data Science need to be redesigned to meet the skill gap challenge.
In recent times, many large corporations and reputed universities have jointly taken initiatives to address the skill gap. One visible outcome of this trend is that in the past five years, Master’s Programs in Data Science and Analytics at American universities have jumped to around 90.
One major skill gap has been identified as data cleansing techniques.
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