ingesting-into-data-lake
byaws· 47 skills
Import data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, or existing Glue catalog tables (migration). Default target is S3 Tables; standard Iceberg on a general purpose bucket is supported where S3 Tables is not adopted. Handles one-time loads, recurring pipelines, migrations. Triggers on: import data, load data, ingest, sync database, migrate table, move data to AWS, set up pipeline, ETL, pull from Snowflake, query BigQuery into S3, export DynamoDB, CTAS, convert to Iceberg. Do NOT use for setting up or troubleshooting Glue connections (use connecting-to-data-source), creating empty tables (use creating-data-lake-table), running queries (use querying-data-lake), finding tables by fuzzy name (use finding-data-lake-assets), catalog audit (use exploring-data-catalog), or SaaS platforms like Salesforce, ServiceNow, SAP, MongoDB, Kafka.
How to install ingesting-into-data-lake?
aws/agent-toolkit-for-aws/ingesting-into-data-lake
$npx -y skills add aws/agent-toolkit-for-aws --skill ingesting-into-data-lakeInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/aws/agent-toolkit-for-aws" --skill "aws/agent-toolkit-for-aws/ingesting-into-data-lake"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/aws/agent-toolkit-for-aws" that are relevant to the current task. Run `npx skills add "https://github.com/aws/agent-toolkit-for-aws"` and select the relevant skills, then follow their instructions.
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