Data.AI is a revolutionary data analytics company combining data and consumer analytics with artificial intelligence to give the sharpest insights imaginable on business decisions. 

Data.AI’s products, ranging from ConnectPlus to the new Total App Revenue, perform a variety of data-driven functions to help companies out, from tracking your own apps’ most critical data usage to gaining visibility of the top monetizing ad platforms. 

As a compliance-first global organization serving major names like Google, Tencent, Visa, and Samsung, Data.AI needs to be on top of cutting-edge developments in all things data, especially data protection.

The Challenge

Running a successful global company with majorly successful customers means the bar is always high. For a company that thrives on data-driven insights and places a strong emphasis on compliance, that means constantly being on the lookout for innovations in compliance to match its own product innovations.

That’s where data mapping enters the picture in theory, but traditionally, data mapping has been extremely difficult and not terribly accurate. 

Data.AI runs a complicated operation, using an unimaginable amount of tech and SaaS tools, so they wanted as concrete a picture of that data map as they could find. It doesn’t hurt either that they, like most companies, get frequent data subject rights (DSR) requests, and have long wanted to handle those as quickly and compliantly as possible.

Risk & Compliance Officer Taufiq Azam was adamant about finding a data mapping solution that could help smooth out the DSR process as well. “For the GDPR, you don’t need to technically conduct a data map, but really you need to do it to understand where the data is and get complete ownership of that, since a broken DSR process can lead to a big fine.” 

The Search for a Solution

As a large company running so many SaaS tools with so much data, Data.AI knew they needed to find the best automated tools available in the data protection industry. 

After testing out several solutions that ranked near the top of G2’s data privacy automation categories, Data.AI felt MineOS was the best vendor since it had the best automation. Taufiq explains, “other tools are only workflow automation, not truly and fully automated—they can’t reach into other SaaS tools and identify them as a data source.”

MineOS’ Radar feature, part of our unmatched continuous data source discovery and classification, especially piqued Data.AI’s interest. Taufiq and the rest of the team choosing a vendor noted Radar “stood out and made things easy, leading to great flow mapping.”  

In addition to how much smoother MineOS’s automation was compared to other options, the little things ended up factoring into the decision as well. From a compliance perspective, Taufiq says, “certain data we need to keep on a legal basis, so anonymization helps majorly and we like the choice that Mine gives to anonymize certain data.”

The Business Impact

After using MineOS’s data mapping for several months, Data.AI now feels it has a more complete picture of their data ecosystem with less manual effort than they’ve ever put into data mapping. 

Taufiq says, “I like what the tool does, and I really didn't want to deal with the workflow prep anymore. After using it for a bit, it’s probably my favorite tool for data mapping.” 

Why is Data.AI so happy with the MineOS platform? They have a firmer understanding of where data is to make DSR management easier, have a baseline for their RoPA reports for GDPR compliance, and save time on intuitive and people-friendly mechanisms that should be the backbone of data privacy.

Taufiq puts it better than we could, “there’s nothing else out there that’s like MineOS, which is why we picked it.”