The Talent Gap In Data Analytics
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According to a recent blog by Villanova University, the amount of data generated annually has grown tremendously over the last two decades due to increased web connectivity, as well as the ever-growing popularity of internet-enabled mobile devices. Some organizations have found it difficult to take advantage of the data at their disposal due to a shortage of data-analytics experts. Primarily, small-to-medium enterprises (SMBs) who struggle to match the salaries offered by larger businesses are the most affected. This shortage of qualified and experienced professionals is creating a unique opportunity for those looking to break into a data-analysis career.
Below is some more information on this topic.
Data-Analytics Career Outlook
Job openings for computer and research scientists are expected to grow by 11 percent from 2014 to 2024. In comparison, job openings for all occupations are projected to grow by 7 percent over the same period. Besides this, 82 percent of organizations in the US say that they are planning to advertise positions that require data-analytics expertise. This is in addition to 72 percent of organizations that have already hired talent to fill open analytics positions in the last year. However, up to 78 percent of businesses say they have experienced challenges filling open data-analytics positions over the last 12 months.
The skills that data scientists require vary depending on the nature of data to be analyzed as well as the scale and scope of analytical work. Nevertheless, analytics experts require a wide range of skills to excel. For starters, data scientists say they spend up to 60 percent of their time cleaning and aggregating data. This is necessary because most of the data that organizations collect is unstructured and comes from diverse sources. Making sense of such data is challenging, because the majority of modern databases and data-analytics tools only support structured data. Besides this, data scientists spend at least 19 percent of their time collecting data sets from different sources.
Common Job Responsibilities
To start with, 69 percent of data scientists perform exploratory data-analytics tasks, which in turn form the basis for more in-depth querying. Moreover, 61 percent perform analytics with the aim of answering specific questions, 58 percent are expected to deliver actionable insights to decision-makers, and 53 percent undertake data cleaning. Additionally, 49 percent are tasked with creating data visualizations, 47 percent leverage data wrangling to identify problems that can be resolved via data-driven processes, and 43 percent perform feature extraction, while 43 percent have the responsibility of developing data-based prototype models.
In-demand Programming-Language Skills
In-depth understanding of SQL is a key requirement cited in 56 percent of job listings for data scientists. Other leading programming-language skills include Hadoop (49 percent of job listings), Python (39 percent), Java (36 percent), and R (32 percent).
The Big-Data Revolution
The big-data revolution witnessed in the last few years has changed the way businesses operate substantially. In fact, 78 percent of corporate organizations believe big data is likely to fundamentally change their operational style over the next three years, while 71 percent of businesses expect the same resource to spawn new revenue opportunities. Only 58 percent of executives believe that their employer has the capability to leverage the power of big data. Nevertheless, 53 percent of companies are planning to roll out data-driven initiatives in the next 12 months.
Companies across all industries are facing a serious shortage of experienced data scientists, which means they risk losing business opportunities to firms that have found the right talent. Common responsibilities among these professionals include developing data visualizations, collecting data, cleaning and aggregating unstructured data, and delivering actionable insights to decision-makers. Leading employers include the financial services, marketing, corporate and technology industries.
Reprinted with permission.