Data is everywhere. Every year we create even more data. As it stands, every two days we create as much data as we created from the dawn of humanity up to 2003. It is a $100B industry, growing 10 percent every year and at the same time, data systems research and the whole industry are going through a major and continuous transition. Given that new data-driven scenarios and applications continuously pop up, there is a continuous need to redefine what is a good data system in such dynamic environments. This course is a comprehensive introduction to modern data systems. The primary focus is on modern trends that are shaping the data management industry right now such as column-store and hybrid systems, shared nothing architectures, cache-conscious algorithms, hardware/software co-design, main memory systems, adaptive indexing, stream processing, scientific data management, and key value stores. We also study the history of data systems, and concepts and ideas such as the relational model, row-store database systems, optimization, indexing, concurrency control, recovery, and SQL. In this way, we discuss both how data systems evolved over the years and why, as well as how these concepts apply today and how data systems might evolve in the future. The recorded lectures are from the Harvard John A. Paulson School of Engineering and Applied Sciences course Computer Science 165.