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Explore every episode of the podcast Little Fluffy PolyClouds: The Data Engineering Playbook

Dive into the complete episode list for Little Fluffy PolyClouds: The Data Engineering Playbook. Each episode is cataloged with detailed descriptions, making it easy to find and explore specific topics. Keep track of all episodes from your favorite podcast and never miss a moment of insightful content.

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1–4 of 4

TitlePub. DateDuration
Episode 1: Mastering the AWS Data Assembly Line23 Oct 202500:18:05

This is the essential guide to Domain 1: Data Ingestion and Transformation—the biggest section (34%) of the AWS Certified Data Engineer - Associate (DEA-C01) exam! We break down the core components of a successful data pipeline. Learn to compare Batch vs. Streaming with services like Kinesis and DMS, master ETL/ELT using AWS Glue and EMR, and orchestrate complex workflows with Step Functions and MWAA. Stop struggling with pipeline design and start building with confidence. Your DEA-C01 success starts here!

Episode 4: The Data Fortress: Securing and Governing Data for the DEA-C0124 Oct 202500:12:20

Lock down your data platform! This is the final domain, Domain 4 (18% of the DEA-C01 exam). We cover essential security best practices: using IAM and Lake Formation for access control, enforcing encryption with KMS (at rest and in transit), and securing network access via VPC and Security Groups. 

Episode 3: The Pipeline Pit Crew: Monitoring, Troubleshooting, and Optimizing Your AWS Data24 Oct 202500:12:36

Keep your data pipelines running smoothly! This episode covers Domain 3 (22% of the DEA-C01 exam). We dive into setting up alarms with CloudWatch, troubleshooting stuck jobs with Glue Logs, optimizing performance and cost in Redshift, and ensuring data quality with AWS Glue DataBrew. 

Episode 2: AWS Data Store Mastery24 Oct 202500:14:16

Where should you put your data? We tackle Domain 2 (26% of the DEA-C01 exam) by comparing Redshift, DynamoDB, and RDS. Learn how to design optimal schemas, use the AWS Glue Data Catalog, and implement S3 Lifecycle Policies to manage data lifespan and control costs. 

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