Yael Elmatad is a Data Scientist at Tapad. Prior to Tapad, Dr. Elmatad was a Faculty Fellow and Assistant Professor at NYU Physics Department, specializing in the use of high-performance computing to study model space parameter optimization. Ms. Elmatad holds a PhD in Physical Chemistry from University of California, and BS in Mathematics, Computer Science and Hebrew Language from New York University. Abstract: With so many tools available to the modern data scientist, sometimes the distance we put between us and our data can have unintended consequences which often makes our tasks more difficult. In my talk, I will discuss how Tapad uses sources of data to build our Device Graph to better connect with consumers in a unified way across their multiple screens. I will discuss how we moved away from using third party data providers to directly examining the source data to remove hidden biases and unnatural correlations. And how, despite sparsity in our source data, we can use that to better model patterns of use.