What Do AI and Machine Learning Mean for DBAs

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Click to learn more about author Patrick O’Keeffe.

Over the course of the past few decades, major trends in technology have shaped and reshaped the role of the DBA in many organizations. As DBAs manage an increasing amount of data, they have also seen an uptick in their core responsibilities – now being tasked with managing more database instances and Database Management Systems (DBMSs) across different platforms both on premise and in the Cloud. Most recently, new data types coupled with emerging applications have led to the growth of non-relational Database Management Systems. Add to this mix, we’re seeing more companies deploy new Artificial Intelligence (AI) and Machine Learning (ML) technologies and toolsets to streamline repetitive tasks and processes.

These emerging technologies  are permeating into the work of the modern DBA, making their lives easier. Organizations are implementing database software that uses ML to help protect customer data and automate the management of their information. They are also adopting tools that make it easier for anyone to deploy a DBMS – even those without any expertise in database administration. DBA employers are also looking for ways to deliver features to their customers based on AI and Machine Learning that will streamline and enhance the user experience.

Out with the Boring…

While the promise of AI and ML is obvious, there is near-term concern among the DBA community that these new technologies could very well take away jobs, essentially automating out parts of their core role. But those with this mindset fail to realize that the introduction of this technology is actually a positive thing, given it can open a wide array of opportunities for employees, especially DBAs, to focus on more strategic tasks across all functions of the business.

In order to thrive in an increasingly autonomous environment, DBAs must learn to embrace the positive effects of incorporating AI technologies and toolsets into their everyday job functions. Many of the tasks that these new solutions help to automate are those found to be the most monotonous, such as installation, configuration, maintenance and troubleshooting, along with patch management.

…In with the Strategic

The adoption of AI and ML technologies frees up time for DBAs to focus their time and effort on strategic tasks that still require a human touch.

Think of roles that require more hands-on supervision, such as risk management and ensuring that organizations meet compliance standards for the upcoming GDPR deadline; who better to handle this than the data stewards themselves? Other essential DBA job functions such as performance tuning will still require close human supervision and will become part of the new core competencies within the evolving role in the wake of AI and ML.

Two New Career Paths Emerging

Many organizations are exploring new roles for DBAs that capitalize on these new core competencies, and two new career paths are clearly emerging thus far as a result:

Data Analytics and DevOps.

DBAs manage large amounts of data, and their experience is crucial to successful Data Science and Data Analytics efforts. More and more organizations are establishing Data Science teams to derive business value from data. Often these teams originate with DBAs or include DBAs, who can provide insight into data that’s being managed, how it could impact areas of the business, what Data Governance is required, and the infrastructure necessary to maintain data operations.

DBAs also have much experience with application change requests that impact database systems. They typically follow a process to ensure that a request is well thought out, is compliant with organizational best practices and won’t have unintended consequences on data performance. These skills are a natural foundation for inclusion in DevOps practices, and DBAs can have a seat at the table for strategic discussions about technology choice, application development and deployment processes.

A More Strategic Future Within Reach

As DBA’s begin to leverage AI and ML technologies and play a more strategic role across the business, leadership will recognize this and begin to  identify other efforts where DBAs can lend their expertise and skill.

DBAs themselves should also seize the opportunity – consider strategic IT and business initiatives underway across their organizations, and evaluate how their broad skill-set could benefit those initiatives. Available online resources and courses can help DBAs sharpen their understanding and learn new concepts, whether they are related to data science or DevOps.

Today’s DBA’s should feel empowered with new, emerging AI and ML applications. Data has never been more important to organizations, and no individual has a better understanding of how to manage and ultimately harvest that data than the DBA.

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