ETL is the process of extracting data from one location, transforming it, and loading it into a different location, often for the purposes of collection and analysis. As Hadoop becomes a common technology for sophisticated analysis and transformation of petabytes of structured and unstructured data, the task of moving data in and out efficiently becomes more important and writing transformation jobs becomes more complicated. Talend provides a way to build and automate complex ETL jobs for migration, synchronization, or warehousing tasks. Using Talend's Hadoop capabilities allows users to easily move data between Hadoop and a number of external data locations using over 450 connectors. Also, Talend can simplify the creation of MapReduce transformations by offering a graphical interface to Hive, Pig, and HDFS. In this talk, Cédric Carbone will discuss how to use Talend to move large amounts of data in and out of Hadoop and easily perform transformation tasks in a scalable way.