What do you need to know in the grand Schema of things?
Having a database scheme is essentially like having a blueprint of your database — it shows you how it’s all laid out, how it’s all organised, and what the relationship is between other tables and data models.
As you’d expect, as you add to your data and adjust your database, overtime the schema is going to get more and more complicated, and often filled with unnecessary complications — the result of which is that you start to see performance levels dropping, and error levels increasing (which frankly, no one wants).
So, what should you do about it?
Give it a good clean!
Optimising your SQL server schema follows a process that seeks to determine the most efficient layout and what techniques ought to be used so that performance, set up, and results are being calculated / generated / optimised to the fullest capabilities of your setup.
There are many different tools and technologies that can be involved in optimising your schema — most popular cloud-based platforms will have specific tools or even automated options that give you the ability to optimise your data; but you might decide you want (or need) to do some manual operations — and this approach is generally a bit more complex.
When you’re looking at the process, you need to (at a minimum) consider:
- Detection of performance problems.
- Monitoring metrics to improve your runtime.
- How complex your schema has become, and what’s been documented.
- Removal of content (and the risks of doing so).
Before you start making any systems changes, you really (really) ought to check when the last back-up was taken and create a new snapshot of the data if it’s not covering everything that’s currently on the system. That way if anything goes wrong — you’ve got a restart point to fall back on!
Once you’ve got your safety net in place, have a look at the platform you’re using and see what analytic and metric evaluation tools are available — running these will give you a good idea of how your schema is currently performing, and what areas are going to need adjusting.
Develop a plan depending on how your results turn out, and what needs to be done in which order — bearing in mind that some data is going to be connected to other data, and so on — and you need to know what altering any of these connection points is going to do overall.
It’s really important to understand the relationship between the data, so your adjustments can be made smoothly and with less risk of removing content that might seem unoptimised but turns out to be performance critical down the line.
It’s always a good idea to keep careful note of what you’re doing, not only to give you a map of what you’re doing now, but for others later to see what’s been done (and why) in order to make further improvements.
If in doubt, most of the schema tools and platforms come with plenty of knowledge and frequently asked questions (FAQs), and there’s usually plenty of chatter in public forums and groups to make use of as well.
Take the time to read what’s available, familiarise yourself with best practices and the latest updates — and in the grand schema of things, you too will have a smoothly running system!
