Just as you’re finally making some progress on getting a data quality solution in place, a new directive comes down and back-burners your work. Data quality gets put on hold for next month. Or next quarter. Or next year.
Sound familiar?
If it does, you’re in good company. Data quality projects get deprioritized in favor of other work all the time, and it almost doesn’t matter whether that other work is legitimately urgent or not. The effect on you (and on your data) is the same… and your data quality issues do not go away.
But even with your effort mandated elsewhere and your budget down to peanuts, you can still make incremental progress on your data quality monitoring. And it’s worth doing that because something is always better than nothing—and hopefully, you’ll be able to leverage the results to get focus and resources back onto establishing a data quality process sooner rather than later.
Here are four key steps to take when you need to deploy bare-bones data quality that puts you in a good position for later, and how GX Cloud can help.
Step 1: Get SaaS-y and minimize overhead
When you need to minimize your effort, a self-service SaaS is the way to go. Because every moment counts: you can’t be spending time obtaining permissions, installing software, or provisioning infrastructure.
At the same time, don’t over-focus on the right now: you need room to breathe (i.e., expand your data quality process) in the future. If that means switching platforms, you’re setting yourself up for extra work. Choose a SaaS option that will accommodate incremental growth.
How GX Cloud helps: You can create a GX Cloud account and start validating your data in just minutes using only your email address. That’s it—GX Cloud is fully hosted and will take care of everything else.
You can start connecting your data to GX Cloud for testing as soon as you create your account. All you need to connect your data to GX Cloud is a set of appropriate credentials.
And for the ‘room to breathe’ aspect, GX Cloud has options for teams at every level, from individual developers to enterprises.
Step 2: Express yourself to maximize impact
When you’re in a deprioritized-data-quality scenario, you need to make every minute of effort yield maximum effects. Meaning that right now, informed and expressive precision is more valuable than undirected surveillance.
Precision is key because it allows you to focus on what you know is a problem. And expressivity is the factor that lets you embed your domain knowledge in the test.
In other words, you know what the data should look like and what kinds of quality problems you’ve had (or fear having). Test for those things to maximize the impact of your efforts. You need to be able to identify specific and relevant issues.
Once you can point to cold hard numbers about downtime prevented and crises averted, building buy-in to expand your data quality is going to get a lot easier.
How GX Cloud helps: GX Cloud’s data quality tests, called Expectations, are extremely expressive by design. They’re simple to build in GX Cloud’s interface and don’t require any coding. That makes them ideal for when you’re crunched for time or can’t give sustained attention to creating tests.
Step 3: Give context to your future self
Part two of “every minute of effort yielding maximum effects” is thinking forward. When a test fails, you’re going to need to do something about it.
There are times when you have the leisure to investigate at your own pace, but resolving data quality issues under pressure is not one of them. You need to accelerate your future work, and that means your data quality alerts need to be as informative as possible.
Time spent deciphering the ‘what’ and ‘why’ of an alert is time you can’t spend resolving it. And you absolutely can’t afford the time to be looking at the results of generic tests and trying to figure out if they indicate a real issue or not.
If you’ve implemented precise and expressive tests, you’re most of the way there! Just make sure the test information gets embedded in the alert.
How GX Cloud helps: GX Cloud can deliver the alerts generated by your precise and expressive Expectations to your email as soon as each testing run completes.
That means each alert puts the context about what failed, how it failed, and when it failed right in front of you. You have the context you need to begin remediating data quality issues right away.
Step 4: Have documentation
If creating documentation isn’t your idea of a good time, it’s understandable. But unfortunately, that doesn’t make it less critical.
Good documentation—documentation that’s complete and up to date—is essential for a project to be effective long-term.
For your data quality process, that means documenting your tests. Each test’s documentation should include what aspect of the data is being tested, what the test is checking for, and the test’s parameters, and it should be updated every time you update the test.
If that’s overhead you don’t have time for, the answer is not to go without docs: it’s to either make the time or find a way to automate their production.
How GX Cloud helps: Expectations are self-documenting. In GX Cloud, every Expectation has an edit history that automatically records its evolution. And every time an Expectation is run, the results include the Expectation’s complete configuration in plain, readable language.
So not only is GX Cloud’s documentation automatic and detailed, but it’s readable for even someone who’s never seen an Expectation before—making it easy to share your results or bring in others when you get a chance to grow your data quality process.
Automatic, detailed documentation that’s readable to anyone is one of the key ways that GX Cloud helps you do more, faster.
If your data quality work is getting deprioritized, take these four steps to deploy an effective set of ground-floor protections for your data.
GX Cloud provides everything you need for fast and simple implementation of a process to protect yourself against critical data quality issues. And because GX Cloud supports the entire data quality lifecycle, it has plenty of room for you to grow your data quality process as and when you’re able.
Don’t let shifting priorities from above keep you from starting to build a data quality process. GX Cloud gives you the tools you need to succeed now and in the future.
