The power of SQL for automation

SQL automation can be life-changing for the database administrator (DBA) who finds their day-to-day tasks bogged down by repetitive jobs. Jobs that, unfortunately, distract from other, more pressing responsibilities. And yet many considerations should be applied when deciding whether or not to automate.

In the best-case scenario, automation saves significant time, allowing DBAs to be more productive. But when used inappropriately it can result in significant errors.

In this article, we look at the power of SQL for automation, and how to use it.

What is SQL?

SQL – short for Structured Query Language – is a programming language that helps manage large chunks of data. It’s used to communicate with databases. Virtually every database uses SQL commands like “select”, “insert” and “update” for navigational purposes. They’ll likely have additional extensions that are specific to that database.

Similar to Python in practical terms, SQL tends to be simpler. It has been the standard language for database communication and navigation since 1986. Unlike many programming languages, SQL uses common phrases and words. So, this makes it easier for anyone who understands English at a basic level to pick it up.

Once you have learned SQL you can use it on virtually any database, to access and manipulate information.

And automation?

The word ‘automation’ is used in many contexts. The basic premise, however, is that it allows tasks to be performed automatically, with little to no need for human intervention. In the context of SQL and data, it could mean automating the creation or navigation of data sets that can then be processed and applied in a structured way.

For example, an SEO agency might use SQL automation to simplify certain tasks that would have otherwise been done by hand. This could allow them to feed keyword sets or other important metrics into multiple workflows, speeding up their work considerably.

Applying SQL for automation

SQL is a relatively accessible way for programmers to automate certain functions pertaining to data. Used in the appropriate context, it can save significant amounts of time and effort.

For example:

·         Backups

A DBA may spend significant portions of their day backing up the database. This is typically the final task of the day. It’s easy, and it usually allows for multitasking, but it’s also not without problems.

For one thing, backups will usually take longer and longer as time goes on. At the beginning, it might take thirty minutes to backup the system. Every day, however, more data is accumulated. This means that the time it takes to back up the system will grow exponentially.

A month or two in, it could take an hour or more. Automation fixes this problem. With an automated backup process, the DBA can backup the system overnight. Then, in the morning, they can check to make sure that the task was completed properly.

This form of SQL automation works because it takes on a job that is constant—never changing regardless of circumstance.

·         Index maintenance

Index maintenance is another task that can be partially or completely automated. DBAs are regularly tasked with rebuilding, reorganising, and updating their index. It’s another process that is both simple to perform yet time-consuming.

Automation may be an appropriate avenue to take. Not all experts recommend this route, with some insisting that index maintenance is a sensitive task that requires a human touch.

DBAs who are on the fence about whether to automate this job might consider speaking to their employers, who might have guidelines already in place.

SQL for automation: to automate or not to automate

Having the wisdom to know when to automate and when to refrain is key to finding success with SQL automation. Certain tasks lend themselves well to SQL automation.

For example, updates, backups, and other maintenance-related tasks are all tedious jobs that can consume a significant amount of human effort. They can also be automated. Automation is often an appropriate solution in these situations because it won’t interfere with other processes.

There are, however, reasons not to automate some SQL tasks. Some of these reasons are purely logistical. If it takes only a few minutes to do a task by hand, but many hours to automate it, more often than not, you’ll be better off taking the manual route.

Other reasons are less about saving time, and more about ensuring a high level of quality in your processes. Some tasks should always be done manually despite the temptation to automate.

One example is the task of checking a database before it is uploaded to a server. This is done to ensure compatibility. It can be automated, but doing so introduces the risk of costly errors that are best avoided.

Indeed, this is the general rule of thumb that should guide your SQL automation efforts. If a task benefits from human oversight, you’re usually going to be better off doing it by hand. If it’s a simple repetitive process, automate it.

Author bio

Ryan Ayers has consulted a number of Fortune 500 companies within a wide range of industries including information technology, healthcare, and AI. After earning his MBA in 2010, Ayers began working with start-up companies and aspiring entrepreneurs in the technology and healthcare space.