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May 2, 2018

Self-Driving Databases are Coming: What Next for DBAs?

Maria Colgan

(Alexandru Chiriac/Shutterstock)

Autonomous is quickly becoming one of the most talked about words in tech. A concept popularized by the automotive industry is quickly gaining traction in other areas, including datacenters.

We’re beginning to see the advent of autonomous databases that leverage machine learning to eliminate human labor and human error. In this new world, the database automatically patches, tunes, backs up and upgrades itself without intervention – all while the system remains up and running.

The idea of a self-healing, evolving and autonomous software taking on human tasks – such as operating machinery – may be unsettling to some Sci-Fi enthusiasts, but others see the vast potential it will have when their jobs are freed from the mundane.

Like the drivers of autonomous vehicles, database administrators (DBAs) find themselves in this position. Half worrying about their future as more and more tasks are automated by self-learning algorithms; half imagining all the new things they will be able to tackle in an autonomous world

As it stands currently, DBAs’ tasks are usually divided between general tasks and those that are specific to the business. The automation of the database means the elimination of most generic tasks such as configuring, tuning, provisioning, backup, or optimization while creating more time for DBAs to focus on business-specific tasks.

These include defining the database architecture and data models for business-critical applications, integrating new data sources, application tuning and end-to-end service level management. In other words, DBAs now have more time to dedicate to creating value by making more data available to more people, along with managing security, which requires experts who understand where the data lives, what the data represents, and which people and applications should receive access to that information.

Less Database, More Data

In that sense, the role is shifting to become less about the database and more about the data itself. As machine learning becomes more prevalent, the DBA role will evolve along with it to become more like a data engineer who can provide deeper insight for key stakeholders and advise them on ways that the data can be utilized to drive the business forward.

(Jozsef Bagota/Shutterstock)

To really have an impact, the DBA – or rather the data architect (DA) – will need to engage more with their business stakeholders who can offer insight into what they hope to gain from their move to new architectures and services, such as the cloud. With all their experience managing data, DBAs can be a critical link in ensuring these transitions go smoothly, and that the right information is accessible in the right places and to only the right people at the point and time of need. Likewise, they should be honing their skills around emerging technologies, such as the Internet of Things, Artificial Intelligence and chatbots, and processing code for streaming data as opposed to batch jobs.

Transitions Take Time

It’s also important for DBAs to remember that the transition to an autonomous environment is not something that will occur overnight. While some organizations have moved their infrastructure to the cloud, many still are using on-premise databases or a hybrid model – all managed by their DBAs.

Just as the company transitions over time, so should the DBA.

DBAs need to embrace the new opportunity they have and enhance their understanding of how data management will evolve to play a critical role in their companies. The amount of available data will continue to grow exponentially. From data sharing services and social media to new IoT and chatbot-enabled applications, the amount of data that can be dissected and analyzed for business intelligence is exploding and has enormous value.

Change Brings Opportunities

Tasks such as data modeling, application tuning and security configuration are proving to be significant in the cloud. It only makes sense that refreshing those skills and expanding on them will become even more important as demand grows. Likewise, understanding the relationships between data and the cloud will be key. For example, honing up on RESTful API scripting skills and orchestration of complete development, test, and production system configurations will make a DBA invaluable to DevOps and strengthen their role in connecting and delivering business systems.

With the number of educational resources available at the click of a button, it won’t take long for a determined DBA to become an in-demand Data Architect who understands the value of data in the cloud and knows what to do with it.

Technology is constantly evolving. Successful IT professionals anticipate and adapt. This wave of automated databases offers new opportunities to ease workloads and keep up with trends creating a positive impact on a company’s success while increasing a DBAs own professional value along the way.

About the author: Maria Colgan is a master product manager at Oracle Corporation and has been with the company since version 7.3 of the Oracle Database was released in 1996. Maria’s core responsibility is creating material and lectures on the Oracle Database and the best practices for incorporating it into your environments. She is also responsible for getting the feedback from our customers and partners incorporated into future releases of the product. Prior to this role; she was the product manager for Oracle Database In-Memory and the Oracle Database query optimizer.  Maria is the primary author of the SQLMaria blog and a contributing author to the Oracle Optimizer blog You can follow her on Twitter at @SQLMaria.

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