If you work with petabyte-scale data, this is for you. It is a complete guide including theory, good practices and practical exercises with a main focus on Amazon Redshift service.
Paweł Hajduk
BigData Cloud Architect & DevOps
For whom?
- Anyone interested in Big Data, in particular those working with peta-byte scale data.
Any requirements?
Previous experience with big data is a plus. No previous experience with AWS is required.
What are the topics?
- Introducing AWS - brief introduction into cloud computing, with emphasis on AWS ecosystem and services available there.
- OLTP vs OLAP.
- Introduction to Amazon Redshift.
- Row vs Column-oriented DB.
- Redshift - explaining cluster types.
- Monitoring of the cluster.
- Multilevel security: data protection, IAM, internal privileges and logs.
- A recipe for designing tables.
- Sorting: Blocks and Zone Maps, explaining compound and interleaved sorting.
- Deep dive into Redshift architecture.
- Ingesting data.
- Copying data - options and good practices.
- Explaining ETL (Extract, Transform and Load) with AWS Glue AWS Data Pipeline examples.
- Explaining ELT (Extract, Load, and Transform) with Amazon Redshift Spectrum example.
- Explaining BI (Business Intelligence) with Amazon QuickSight example.
- Introduction to Data Lake.
- Practical exercises with Amazon Athena, AWS Lake Formation and AWS Glue.