Big data plays a role in almost every industry and is rapidly becoming a key driver of business growth and competitive advantage. One of the primary benefits of big data is its ability to turn data into potential revenue. This has created an information-based economy that is growing as companies continue to use data to discover new insights and make better decisions, which helps professionals innovate, improve and optimize businesses.
The potential for big data to add to a company’s bottom line is fueling tremendous growth in the emerging job sector. Many are predicting that there will be a shortage of qualified employees available to meet the need for data analysts and managers who will be able to effectively use big data to make significant decisions. While big data may grow significantly across many industries, much of the growth will likely be in industries related to computer and electronic products, information, finance, insurance and the public sector.
Despite the lack of standardized job titles under the big data umbrella, most big data jobs can be grouped into four main classifications of skillsets.
Data scientists, often at the top of the big data hierarchical chart, are typically proven professionals who possess deep analytical talent. They typically have bachelor’s or master’s degrees in artificial intelligence, natural language processing or data management and have strong backgrounds in mathematics or statistics.
Data architects are computer programmers who are skilled in working with undefined data and disparate types of data. They are comfortable dealing with ambiguity and have the persistence to resolve data issues and develop innovative ways to use data to gain new information. They typically have a traditional programming or business intelligence education and background.
Data visualizers are professionals who are able to translate data into information that people can effectively use. They explore data to identify what it means and what impact it will have, and then present the information in terms that non-technical staff and management can fully understand. They are skilled business analysts with excellent communication abilities.
Data change agents use data analytics to recommend and drive changes within an organization. They often come from a process improvement background, such as Six Sigma. They, too, must possess strong communications skills.
Data engineers and operators are the designers, builders and managers of big data systems. They often have experience as IT or IS systems analysts. They are the architects behind systems and are responsible for making sure those systems perform correctly and provide a business with the data it needs.
Data analysis is the cornerstone for most big data positions and employers expect candidates to have strong analytical backgrounds, including education and experience with data analysis, business analytics, mathematics and statistics. A scientific temperament that leans on strong quantitative skills with the ability to be agile is also a high-demand skill set.
In addition, employers are looking for those with an intense level of curiosity who are capable of working at the intersection of several different business domains. They must be able to take ideas and concepts from one field and successfully apply them to another and must be comfortable with a high degree of uncertainty. They also need to have a high level of creativity in terms of developing solutions and solving problems, along with the ability to effectively communicate with technical and non-technical people at all levels of an organization.