Data Quality Best Practices for Today’s Data-Driven Organization
These four best practices will help ensure your data is of the highest quality.
Just a few years ago, data quality was about as exciting for many people as watching broccoli grow. Today it has become a critical strategic issue for two key reasons. First, a wave of strict new data privacy regulations has put compliance high on most CIO’s lists. Second, in an increasingly data-driven business environment, you can’t compete effectively without high-quality data.
Our field has grown a great deal in a short time. A recent Forbes article notes that nearly two-thirds (63.4 percent) of Fortune 1000 firms now have a formal chief data officer (CDO) compared to just 12 percent in 2012. The data governance market is predicted to grow to over USD $2 billion by 2022.
One good thing about all this growth is that several clear best practices for data quality have emerged. In this article, I will highlight four of the most important ones.
I won’t try to tell you what the best data quality solution for you is, but I can tell you what the worst one is: the one that didn’t get used when it should have been. This is why it is critical to have a solution that integrates into your current automation environment instead of relying on standalone capabilities for such tasks as data validation and verification.
We are in the middle of an API revolution where cloud-based tools link your CRM, marketing automation, or other platforms to tools such as USPS databases, geolocation, lead validation, and much more. IBM and others have dubbed this trend the “API economy.” Using an API strategy lets you engineer these tools directly into your data flow at the time of data entry or use.
Contact data goes bad at a frightfully rapid rate. According to at least one source, over 70 percent of B2B contact data decays over the course of a year as people move, change jobs, or get new addresses or emails. This doesn’t even count how much of it is wrong, fake, or fraudulent in the first place. Your inbound contact data unfortunately includes everything from mistyped addresses to people supplying bogus information to get your latest free marketing giveaway.
This means you must validate data at the point of entry and time of use each and every time you use it. This requires having the right tools and the right processes.
