At WWDC 2019, Apple debuted the “Sign in with Apple” feature, a new authentication system similar to those offered by Facebook and Google, but with privacy-enhancing features, including the ability to hide your actual email address—providing unique email addresses for each service you log in to.

In an exclusive interview with CBS News’ Norah O’Donnell, Apple CEO Tim Cook noted that “the user wants the ability to go across numerous properties on the web without being under surveillance. We’re moving privacy protections forward. And I actually think it’s a very reasonable request for people to make.”

That request, however, can make the lives of data analysts more difficult—customer data is tantamount to liquid gold for practically any consumer-facing industry. Data, including purchase records, website/page visits, marketing email open rates, support tickets, and in-store interactions are associated with online transactions. These—and others—are all important signifiers that companies aim to unify for tracking individual users, as well as aggregating into market trends.

SEE: Special feature: Managing the Multicloud (TechRepublic)

Kazuki Ota, founder and CTO of Arm Treasure Data, is upfront about the impact Apple’s plans could have. “With that type of solution, our match rate will be decreasing for sure,” Ota told TechRepublic, but cautioning that “The effectiveness of this Apple move was more about how the email address will be used. That prevents certain actions, but I think the effectiveness, personally, will be limited.”

Creating pseudo-anonymous IDs that aim to limit tracking is a hurdle that enterprises have already cleared. “A lot of enterprises—especially larger ones who have been operating for more than 100 years—they have a lot of acquisitions, multiple businesses and multiple brands,” Ota said. “A typical customer has around… 13-14 customer IDs. Let’s say I interact with one group, and they have multiple brands. They might have information scattered across these brands.”

Treasure Data’s ID Unification feature can take attributes of multiple IDs and combine them into one profile across data sources. “Eighty to 90% of the work of creating this type of clean profile is actually having a lot of clean-up process of the data and also having a higher quality data,” Ota said. “It won’t be perfect, to be honest, because 100% clean data is almost an imaginary situation.”

For more, check out “OpenID Foundation says ‘Sign In with Apple’ is not secure enough” on ZDNet, and “What does a cloud data warehouse look like?” at TechRepublic.

Ronnie Chua, Getty Images/iStockphoto