Here, we define what we mean by “dirty data” – how common it is, where you can find it, and how you can fix it.
What do you think of when you think dirty data?
There’s no dictionary definition of the term, but when we in the commercial real estate software space talk about dirty data, we’re talking about data that’s incorrect, incomplete, or miscategorized. Have a client in your CRM with multiple last name spellings? That’s dirty data.
Dirty data is born of inaccuracies, poor processes, and/or inadequate software solutions. All of these risk factors are facilitated and exacerbated by spreadsheet software – so, no surprise that Excel is where a lot of data go to get dirty.
So, how common is dirty data?
Pretty common, it turns out.
“The only time a company could have clean data is on day one,” says Daryl Pitts, Pereview’s senior vice president of sales. “And even on day one, they may have compromised venture capital or start-up data.”
Therefore, don’t feel bad if you’ve discovered some dirty data-related issues at your firm. The problem is not exclusive to any specific type of company and is not necessarily an indictment on how you run your business. Nevertheless, it can have grave consequences on how business gets done.
Dirty data is the digital equivalent of a red shirt hidden inside your white laundry; many companies don’t spot it until everything is pink.
The team at Pereview can help you identify existing dirty data, clean it, and keep it clean by aggregating all of your data into one place. An all-in-one solution for commercial real estate asset management, Pereview is the only Life of the Asset™ solution on the market today. It integrates siloed systems and processes, allows for push-button reporting, creates a Single Source of Truth, and establishes standard workflows and guidelines for asset and data management.