What did the developer say to the DBA? It doesn't matter, the answer is "no." I've never worked with a database administrator (DBA) before but know they play an important part in the data lifecycle at a company. Sean Scott stumbled into the DBA world and has been in this field for 25+ years. He started his career working at a consumer electronics manufacturer. He started building his data chops as an inventory analyst and eventually got into the world of Oracle database migrations and application development. This episode explores a perspective on data we don't normally see: from the DBA. I think it's important to understand this perspective since data and business analysts ultimately use the data that is transformed and formatted by DBAs.

I remember saying I will never be a DBA

Sean likes to poke fun at the DBA crowd and remembers telling someone at a party he would never become a DBA. Perhaps his tongue-and-cheek attitude towards DBAs is what makes him so successful as a DBA. He currently works at a company called Viscosity where he does database and application development.

In short, I solve puzzles.

Sean explains how his background in data analysis and DevOps has helped him in his career as a DBA. This area of data is beyond my area of expertise, but Sean was able to relate things back to why this area matters for data analysts. Despite being in a "technical" role, Sean discusses the other qualities that make a DBA (or anyone in a technical role) successful:

The best technical people I've met have had great people and business skills.

How data analysts can work with DBAs better

What does DBA stand for? "Don't bother asking." That's Sean's favorite DBA joke. From a data or business analyst perspective, Sean says DBAs are typically seen as people who restrict access to data. DBAs can sometimes be seen as barriers or just standing in the way. Sean's advice to data analysts and the consumers of data in organizations is to help change the perception of what DBAs do. I love this extremely outdated video explaining what DBAs do:

https://www.youtube.com/watch?v=74j_foRlM5U

Sean says many DBAs fail to see the difference between data and databases. Many tend to mix the two together, but Sean believes these two concepts should be thought about and treated differently. Data analysts should seek to work with DBAs to understand where their data comes from. This leads to an important concept I haven't heard of until this conversation with Sean: data as code.

Data as code leading to a diversity of ideas

Sean says that DBAs may think of data as being very fragile and brittle. They have this perception that data needs to be restricted or else it might be deleted when it's in the wrong hands. That's because DBAs aren't thinking of data like other parts of the DevOps process.

Infrastructure as code has become a well-known concept as DevOps engineers manage data centers in the cloud, why can't this same concept be applied to data? We can apply automation and configuration to the management of data. DevOps is typically concerned with storage and networking. The data lifecycle and pipeline can also be added to this list to "harden" data for the enterprise.

Now the actual nuts and bolts of this stuff is way beyond my pay grade. The benefits to data analysts, according to Sean, are plentiful. Analysts typically just analyze the data but don't have much experience managing the data on their own.