With the rise of modern data platforms and cloud-based solutions, BI has become just one part of a much larger data ecosystem. This evolution has presented data teams with a host of new challenges, primarily in terms of the skills and expertise to create and manage data products that meet the needs of data consumers.
Lift-and-shift is potentially a very efficient method to move your applications to the cloud. You need to be aware, though, of the implications of the pay-as-you-go pricing model that comes with a cloud deployment. Check out our 3 tips to ensure lift-and-shift delivers the most cost-effective solution.
AWS Glue, the serverless ETL service of AWS, supports two types of jobs: Spark and Python shell. In this article, we'll focus on Python shell jobs and explain how you can make optimal use of your S3 Data Lake using Athena within Python shell jobs.
Chances are you have recently heard a lot about data mesh, a decentralized approach to sharing, accessing, and managing analytical data. So, let's dive into a practical example to help you understand what a data mesh stands for.
