How Has the Role of the DBA Changed?
The role of the database administrator has been expanded to include data management, infrastructure, and workload/SLA management.
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To gather insights on the state of big data in 2018, we talked to 22 executives from 21 companies who are helping clients manage and optimize their data to drive business value. We asked them, "How has the role of the DBA changed as part of the big data strategy?" Here's what they told us:
- The emergence of the data ops concept. Data management and data governance. Many players are all part of the value chain, with roles based on certain assumptions. Data operations is part of the team, with shared goals collaborating with when data is collected and created. How to use automation to squeeze out delays. Agility to take the most appropriate action. Drive greater efficiency and value.
- Management, as well as governance and software delivery. Maintain database models and schemas. In big data, everything is exploratory — not relational. Shift from well-defined to enabled for applications and engineers to work together collaboratively. Manage meta-data discovery.
Infrastructure and Platforms
- It's quite a challenge, as they are no longer in control of the database technologies that the applications use. The more that’s moved to the cloud, the less the DBA has control of. There are more data and more databases.The skill set of managing data infrastructure, proposing solutions for large amounts of data, integrating, knowing how to archive, and handling disaster recovery. AWS seems to tie database options in the cloud to DBAs. They still have to worry about backup, disaster recovery, and massive storage. Need to think more strategically with regards to backup and storage.
- It depends on how you view the previous or current roles of DBAs. For this, I’ll start by stipulating that DBAs, in my opinion, have always needed to be part of the entire software development process. In today’s problem sets, it’s now more imperative than ever to have all DBAs engaged throughout the development process, especially planning, scoping, and prototyping. DBAs can provide concrete information on items such as data infrastructure capability, cost of needed changes, potential performance impact, and overall capacity planning (there’s a strong desire for this to be predictable).
Workloads and SLAs
- There are many more technologies to manage than ever. You’ll have a data warehouse and ten to 20 technologies to understand and manage. You need to understand the technologies and what will make it easier for the DBA to do online and scale out. Pick the right technology for the right problem. Larger companies are looking at standardizing a group of technologies for search, NoSQL, Hadoop, and GPU so that they require less management and administration.
- Adapt scripting and automation to end users.
- It varies by company. With previous generations of Oracle and Teradata, you needed a DBA. Now, with enterprise architectures evolving to open source and the Hadoop ecosystem, the expertise lies with the developers rather than the DBAs. DBAs need to evolve to be more developer-facing.
- Data is more mainstream and dominant. DBAs have evolved into more sophisticated insights and writing scripts. More upstream and complex.
- In a world of real-time data, the roles of DBA and DevOps are changing significantly. Decentralized data applications need a new set of tools for management.
Here’s who we spoke to:
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