Amazon Redshift and the “Low/Zero-Code - Low/Zero-ETL” narrative
Amazon Redshift is a column-oriented, fully managed, petabyte-scale data warehouse that makes it easy and cost-effective to analyze all your data. It achieves efficient query performance through a combination of massively parallel processing, columnar data storage, data compression, and ML powered system optimizations. In this blog let's look at how Amazon Redshift helps the “Low/Zero Code – Low/Zero-ETL” narrative. Before we get started, let's first understand what ETL means and why we do ETL. ETL stands for Extract, Transform and Load, and it means exactly what each of these terms sounds like. We Extract data from a source, Transform the data based on the need and Load it to a target. For example - You can use a Cobol program to Extract data from a GDG, Transform the data in a series of Cobol code and Load it into a DB2 table. Another example can be where you use an ETL tool such as Informatica or Talend to extract data from a table or a file, Transform the data and then L