Challenges and considerations when building a data lake on Amazon S3

When building a data lake on Amazon S3 or data lake in general, here are some challenges and considerations one should be aware of:

• Data ingestion: The process of bringing data into a data lake can be challenging, particularly when the data comes from multiple sources with varying formats and structures. This can lead to difficulties in ensuring data quality and consistency. Additionally, handling large volumes of data can be a challenge, particularly as the data grows. Another issue is keeping schema changes consistent throughout all downstream applications.
• Data governance: Maintaining data quality, security, and regulatory compliance can be difficult when dealing with a large volume of data in a data lake. Implementing policies and standards for data classification, quality, and retention, as well as managing access and permissions, including role-based access control (RBAC) and data encryption, can...