Posted in SQL Server, T-SQL Tuesday

T-SQL Tuesday #138 – Managing Tech Changes

It’s the second Tuesday in May so it must be T-SQL Tuesday! Thanks to Andy Leonard (b | t) for hosting this month’s blog party. (As always, you can read up more about T-SQL Tuesdays here.) Here’s his invitation:

For this month’s T-SQL Tuesday, I want you to write about how you have responded – or plan to respond to – changes in technology.

There are a couple of ways tech changes on you:

First, there are the changes that occur because something is “fixed” or improved when the newest version is released. For example, upgrading SQL Server versions gives you fixes to things like Cardinality Estimators and Intelligent Query Processing. These sort of changes will either suddenly speed up\wreck havoc on your performance whether you expect it to or not. But to me, these are also the sort of changes that could happen if you suddenly have a new index or the amount of data in the table drastically changes or your dev dataset size was significantly smaller than what was in production or your statistics are out of date, etc.

All we can do in these cases is test what we write to the best of our ability and adjust based on the new conditions. Sometimes, we can predict what will happen and can plan for it before it goes into production. Other times, we will learn the hard way. But I feel like these are expected and we just need to roll with these as we find them.

Then you have the changes because what you had been working with has been completely restructured and reimagined. I’m looking at you, SSIS changes from SQL Server 2008 to 2012. The introduction of SSISDB and the idea of environments, along with some of the other improvements made in general, were pretty drastic changes and if you had SSIS packages, you had to figure out what the changes were and how you were going to support them. I worked at one place where things were pretty much kept as they were. And I worked at another where the clients on SQL 2008 had SQL 2008 packages but we updated the model and structure for SQL 2012 and higher so we could take advantage of the new structure. Being about to take advantage of environments meant that we had a really easy way of deploying to clients and setting things up as part of the install\upgrade process.

For changes like these, we need to understand what the changes are and how we need to adapt our current code to those changes. We usually get some warnings about these features so the key is to try to get ahead of the releases or make sure we can test them in a dev environment before the client decides to upgrade on us and we find ourselves learning in production.

And then there are the shiny brand new features or technology. These are the things that the latest buzz words are built around.

Sometimes I feel like an old curmudgeon when it comes to new tech. I feel like I come across as anti-new-tech when it’s proposed as a solution. If it’s not something that I know, I want to understand it first. But the reason I feel like I come across as opposed to the changes is I will hear about it in terms of “we’re having problems with ABC so let’s just replace it with FGH”. What I don’t hear is how have we tried to fix ABC or is the problem with ABC really something that is solved by FGH. Or I’ll hear a misunderstanding of how FGH works so it becomes clear that not only do we not understand what the problem is that we’re trying to solve but also we don’t understand how the new tech will actually be able to help. It sounds better to say we’re implementing the new tech and we’re tech forward. But this approach means that we find ourselves not solving the initial problem along with creating new ones.

Don’t get me wrong – the capabilities of the new tech and the problems that they can solve are really cool and exciting. But we end up treating the new tech as the solution rather than the tool used to implement the solution. So we never get around to the underlying issues and we blame the new tech for not solving the issues rather than our lack of understanding of what we need to set up for the new tech to help.

The solution here is to go back to understanding the problem we’re trying to solve. This is where we need to learn what the new technology changes are for, understand how they work, think about the problem they solve, and then figure out if they will work for the problems we’re trying to solve. In many ways, I don’t always get a chance to play with the new tech because I’m too busy trying to see if I can solve with what I have available already. But the key I find working with these sort of new tech changes is education. We have to educate ourselves as to what the new tech is and then educate others as to what it is.

In many ways, education is the key to all of the different ways that tech changes on us. That’s why I’m here and that’s why I try to go to the different Data Platform events when I can. We have to be open to learning about and embracing these changes. In the end, we have no choice if we’re going to stay on the top of our game. But it always comes down to understanding the problem we’re trying to solve and what role the changes in tech have to play in it if we’re going to be successful.

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