Data-driven roles are in demand. According to research firm Deloitte, the number of postings for positions in data science, data engineering, machine learning (ML), and visualization now surpasses those for more familiar skill sets such as customer service, marketing, and public relations (PR).
For database administrators (DBAs), business technologists, and data engineers, this increasing demand comes with the opportunity to explore new roles within their organization and expand existing skill sets to make better use of emerging technologies.
But what comes next? Beyond the growing need for skilled data staff, what does the future hold for this trifecta of technology professionals? How will these roles evolve over the next few years to align with the growing impact of cloud technologies, Internet of Things (IoT) deployments, and the increasing use of artificial intelligence (AI) and machine learning (ML) frameworks?
The Database Administrator: Delivering Dynamic Architecture
DBAs are responsible for managing, monitoring, and upkeep of SQL, NoSQL, Oracle, and other database environments. The advent of process automation and machine learning tools, however, has led to questions about the future of this role: If software tools can handle most of the heavy lifting when it comes to repetitive and error-prone tasks, where does that leave DBAs?
Moving forward, database administrators should expect a shift in priorities that sees them focusing on the dynamic nature of database architecting, capacity planning, and scaling to help businesses reliably access and leverage data across multiple clouds and on-premises instances. Put simply, the role of DBAs is shifting away from managing databases to assisting organizations in making the most of evolving and interconnected database architecture.
The Data Engineer: Abstracting the Source
Data engineers leverage their expertise to discover trends and develop new algorithms that help companies pinpoint actionable information within data sets. Historically, data sources defined the scope of this work—each unique source required its own set of processes and algorithms to facilitate effective data capture.
Consider user data stored across different databases. While the underlying asset—the user—remains the same in each case, disparate data sources meant different analysis models for each. Once extracted and formatted, data from different sets could then be combined to facilitate trend analysis and strategic decision-making.
The future of data engineering, however, is about abstracting the source. By leveraging both machine learning algorithms and AI frameworks, new engineering approaches are capable of capturing and understanding data in a way that’s set- and source-agnostic.
The Business Technologist: Finding Common Ground
Business technologists often have a combination of operations and development skills—for example, they may be data analytics experts who also have experience designing and building applications. This diversified expertise empowers technologists to help improve communication and collaboration across multiple departments. By functioning outside the traditional paradigm of IT, business technologists are better equipped to see the bigger picture and identify opportunities for increased efficiency.
The ongoing integration of IT into business processes at scale, however, sets the stage for an evolution of the business technologist role that broadens their communications strategy. This starts with the C-suite. To secure executive support and ensure appropriate funding for new IT projects, business technologies must now bridge the gap between technical and tactical communication to capture C-suite attention and encourage specific action.
There’s also a growing need for business technologists to cultivate connections with outside experts such as managed service providers. From data backup and disaster recovery solutions to on-demand data management platforms, there are now a host of solutions that can make business operations easier—if companies can pinpoint where they’re best used and how they can integrate with current operations.
The Evolving Future of Data Expertise
In the near term, data professionals will see increasing demand for their skills as businesses look to effectively leverage the volume, variety, and velocity of information produced across their networks.
Over the next few years, however, members of this technology trifecta should expect changes in their roles as technology continues to evolve. For DBAs, this means a move away from static management and monitoring to dynamic architecting and scaling. For data engineering staff, a shift to source-agnostic data analysis is on the horizon. And for business technologists, communication is key—not just across departments but outside traditional boundaries to leverage the potential of provider-driven expertise.