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Author: way0utwest
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Database Brainstorming
I read a post recently that captured my attention for more time than I expected. The piece fascinated me, and I sent it to my son and a couple friends. In fact, reading it caused me to stop working for a bit as I thought through some of the concepts and ideas. It’s about divergence and convergence, and how you can use these ideas when trying to be creative. I recommend you take a few minutes and go through it.
Is this something we ought to do a bit in database design? Should we spend first some time on divergent, creative thinking for how to implement some new entity or design some schema? Do you ever do this in your job, especially in a team? Or do you just push forward with your first thoughts, relying on experience and instinct? That’s what I’ve often done.
We certainly need convergence thinking. We have to get things done and deliver software. Most of us are probably good at the convergent side of thinking and writing code or queries or configuring systems. Most of us probably do some amount of divergent and convergent thinking at the same time.
However, I’m not sure that’s the best way to tackle creative work, especially when building complex systems or working to solve new types of problems. There is some value in separating out the brainstorming portion from the actual, let’s write some code and see if it works. Getting a good list of potential ideas and spending a few minutes thinking about them before writing code helps us to avoid getting trapped pursuing into the first thing that works and possibly see other approaches.
In today’s world of DevOps, trying to move faster and get small chunks of work to the customer quicker, we are under pressure to do more convergent work, quicker. If we want to ensure we do model our entities well and follow good database design practices, we need to spend some time with divergent thinking without doing work, perhaps speculating on potential future design challenges in advance. If we periodically spend this time, then we can rely on our previous brainstorming when it is time to converge and get things done.
Steve Jones
The Voice of the DBA Podcast
Listen to the MP3 Audio ( 2.3MB) podcast or subscribe to the feed at iTunes and Libsyn.
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Pausing the Learning for March
In my last update, I was disappointed with my February progress. Busy with life and work, I didn’t do much reading or practicing. The latter is really the important part.
I started March thinking I’d do a bit more, but I realize that won’t happen. I tried a little over the weekend, but with coaching responsibilities and family items, I just couldn’t really focus.
March is a busy month for me outside of work. I have 3 major weekend volleyball tournaments with my daughter and my team, some travel for work, and still family commitments. In addition, I’ve started authoring a course with Packt, so my nights will be busy.
As a result, I’m going to pause learning for March. Once I get past a few of these deadlines, I’ll go ahead and start reading again. For now, March will be heads down with SQL Server 2019.
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Common Data Challenges
Working with data has proven to be a challenge for most of my career. It’s been fun, and certainly fulfilling, but there are constant challenges involved. Let’s take away the hardware and admin challenges of keeping systems running, backed up, and performing well. I’m thinking today of the struggles of just data.
There is a short article that talks about three common data issues, and these are some of the same ones I’ve struggled with for most of my career. Are these challenges any different than they were 20 or 30 years ago? I’m not sure, and I was working with databases and software nearly 30 years ago.
ETL is a constant challenge, even today with tools like SSIS and Biml that make it much easier to build flows that migrate data from one database to another. ETL is such a challenge that many people make a very comfortable living helping organizations meet their every changing needs to move and prepare information for end users.
The other challenges noted in the article are getting a complete data picture because of missing data and not trusting or believing in data. The latter hasn’t been as much of a problem for me. I might describe it differently as more often we aren’t sure what weight to place on certain data. The world is messy, and often we collect data that we think might be valuable only to realize later that it doesn’t mean what we thought or our our hypothesis was incorrect in the first place.
I think the challenges are part of what makes this work interesting. Our employers and clients might view the effort and time involved as frustrating, and I wish I had solutions to make our process quicker and smoother. Actually, I do think that advances like SSIS have made things quicker, but the world has grown more complex. We deal with more data from more systems, in the still chaotic, messy formats of the world.
What are your challenges with data today? Are they getting better, worse, or still the same as they always were?
Steve Jones
The Voice of the DBA Podcast
Listen to the MP3 Audio ( 3.4MB) podcast or subscribe to the feed at iTunes and Libsyn.
