AWS Data Lakes

1. Scalable Storage: Amazon S3 provides scalable, durable storage for data lakes of any size.

2. Data Ingestion: Tools and services for ingesting data from various sources into the data lake.

3. Data Catalog: AWS Glue Data Catalog for organizing and cataloging metadata to facilitate data discovery and analysis.

4. Data Preparation: AWS Glue ETL capabilities for preparing and transforming data before loading it into the data lake.

Before learning AWS Data Lakes, it's beneficial to have the following skills:

1. Cloud Computing Fundamentals: Understanding of basic cloud computing concepts and familiarity with AWS services.

2. Data Management: Knowledge of data management concepts, including data ingestion, storage, transformation, and analytics.

3. Big Data Technologies: Familiarity with big data technologies such as Hadoop, Spark, and NoSQL databases.

4. Data Warehousing: Understanding of data warehousing concepts and technologies for storing and querying structured data.

By learning AWS Data Lakes, you gain the following skills:

1. Data Ingestion: Ability to ingest data from various sources into the data lake, including databases, streaming data sources, and IoT devices.

2. Data Organization and Cataloging: Skills to organize and catalog metadata using AWS Glue Data Catalog to facilitate data discovery and analysis.

3. Data Preparation and Transformation: Capability to prepare and transform data using AWS Glue ETL capabilities before loading it into the data lake.

4. Security and Compliance: Knowledge of security best practices and access controls to protect sensitive data and ensure compliance with regulations.