The goal of Phase Analytics is to present concepts from digital signal processing (DSP) that are important to data scientists. Many data scientists come from computer science, mathematics, or other various backgrounds and may be unfamiliar with digital signal processing. But why is DSP important for data science? Modern machine learning algorithms, i.e., deep learning, operate on raw signals such as images, videos, and speech waveforms. These signals fall in the realm of DSP, and have many nuances that can impact the performance of machine learning algorithms that operate on them. My goal with Phase Analytics is to show data scientists some of these nuances and help the community improve their machine learners.