Forbes calls big data and analytics and big data — the processes and technologies that manage substantial data sets that develop at lightning speed — “the oil of the fourth industrial revolution,” the grease of the first three being water and steam, electricity and assembly lines, and computerization.
Hardware and software now build and optimize algorithms in real-time; automated data visualization digests digits and returns simple-to-understand maps; augmented reality adds an all-new dimension to the value of data by supporting customer-service bots. These are just a few elements in the fourth revolution’s lubricant.
For all that automation, however, the human element persists. This insight validates Harvard Business Review‘s 2012 prediction that data science would be “the sexiest job of the 21st century.” In this context, “sexy” means jobs with rare qualities that are in high demand.
Why Is Data Analytics the Job of the Future?
As new technologies emerge, enterprises are deploying them not only to improve every business operation but also to innovate new systems and processes that add ever-increasing value to data and analytics.
Analytics Insights notes several emerging forces driving the growth of big data and analytics that help companies make efficient and effective decisions. They include:
- The ability of cloud software to track and analyze volumes of business data as transactions occur, enabling real-time optimization of resource allocation and processes with confidence in positive outcomes
- A drive toward self-service business intelligence analytics that deliver on-demand data visualization, inputs that support operational decisions, insight into customer service trends and develop models and make conclusions
- The worldwide adoption of predictive analytics that forecast future market trends will grow by 25%, reaching a total investment of $22 billion over the next five years
Moreover, as the adoption of artificial intelligence (AI) continues to grow, the value of data professionals will also. Analytics Insights defines AI as the results of processes that automate workflows, optimize logistics and mine data that provides meaningful knowledge about assets, brand positioning, personnel and the market. “While AI is likely to continue to develop, we aren’t yet near the point where it can do what humans can … spot anomalies and threats in an efficient manner,” it notes.
What Is the Job Outlook for Data Professionals?
In a separate article, Analytics Insights notes that data analytics are at the core of businesses in every sector of the global economy and growing. As a result, demand for analytics experts is outstripping supply as enterprises discover new ways to harness data.
“This is occurring universally and isn’t limited to any part of the world. Despite big data analytics being a ‘Hot’ job, there are as-yet countless unfilled positions across the globe because of a deficiency of required expertise,” the publication reports.
That demand creates opportunities for information-systems professionals with graduate degrees in business analytics for advancement to executive positions such as chief information officer, systems analyst, information architect and more.
What Skills Do Data Analytics Professionals Have?
The increasing premium that businesses place on data and analytics requires broad expertise regarding the deployment of new database software as it becomes available; implementation of project-management processes; and knowledge to mine, organize and analyze data for trends, patterns and insights.
The Master of Science in Information Systems with a Concentration in Business Analytics online program from Murray State University equips graduates with those skills through coursework that covers:
- Areas outlined in “A Guide to the Project Management Body of Knowledge (PMBOK Guide)”
- Enterprise resource planning, software integration and business decision-making that are all related to ERP systems
- Software cycle, software process maturity and Agile modules
- Software methodologies such as object-oriented, rapid development, software design and verification and testing