A New Need for AWS ETL Tools
As many companies transition their analytics initiatives to cloud platforms, Amazon Web Services (AWS) is a top pick. Offloading data management expenses are a big reason why companies turn to the cloud; as such, many companies will also choose to leverage Amazon Redshift, a fully managed data warehouse, on top of AWS.
Migrating to AWS and AWS Redshift is a multistep process that is typically part of a larger enterprise transformation effort. One of the many questions that inevitably surface during this transformational period is how to do AWS ETL (Extract, Transform, Load) or more specifically, AWS Redshift ETL.
Under traditional data warehousing, ETL was often handled by a small technical team that would standardize and cleanse data before it was made available for business use. Certainly, a like-minded approach to AWS ETL exists today; to move data in and out of Redshift, companies can build a custom Redshift ETL pipeline or leverage an existing AWS ETL service.
However, the downside to these AWS ETL approaches is that they are limiting given their technical nature. Only IT can do AWS ETL. That means that business users are
Inevitably left waiting, if not for days then for weeks, to gain access to the data they need. On top of that, IT rarely has the deep business understanding needed to identify the insights and additional questions that can help to reshape the data during the AWS ETL process in new and useful ways.