This document discusses Apache Dremio, an open source data virtualization platform that provides self-service SQL access to data sources like Elasticsearch, MongoDB, HDFS, and relational databases. It aims to make data analytics faster by avoiding the need for data staging, warehouses, cubes, and extracts. Dremio uses techniques like reflections, pushdowns, and a universal relational algebra to optimize queries and leverage caches. It is based on projects like Apache Drill, Calcite, Arrow, and Parquet and can be deployed on Hadoop or the cloud. The presentation includes a demo of using Dremio to create datasets, curate/prepare data, accelerate queries with reflections, and manage resources.