Master Open Data Lake Architectures
One of the hottest trends in the data industry is the emergence of table formats such as Apache Iceberg, enabling the data layer of the analytics stack to be centralised between many engines. This offers great flexibility, but with some important trade-offs, particularly regarding federated governance and cataloging.
Join Snowflake, Slalom and AWS for an engaging half-day workshop where you’ll dive into the latest advancements in open data lake architectures. Learn how Snowflake’s Apache 2.0 OSS Iceberg catalog, Polaris, and other tools can help you unify data on S3 while offering federated access through various query engines such as Snowflake, Spark, Flink and Trino.
Anchoring on Financial Services, we’ll explore the motivations for unifying your data layer using Apache Iceberg, and dig deep into the practicalities of doing this today. We’ll close out the session by guiding you through a hands-on lab across Snowflake, Slalom and AWS so that you can test the concepts yourself!
What you’ll do:
- Explore the benefits and trade-offs of adopting the Iceberg table format
- Gain insights into Snowflake’s support for Iceberg and open-source standards through the Polaris Catalog project
- Understand the key challenges of designing an open lakehouse architecture with Snowflake, Slalom and AWS, focusing on unifying data governance and managing disparate data catalogs
- Learn about best practices to overcome these challenges
- Get hands-on experience building an open data lake using Snowflake and AWS Glue as engines on top of Iceberg data
Target Audience:
- Data engineers interested in leveraging Snowflake, Slalom and AWS to build scalable, open data lakehouse architectures.
- Data or enterprise architects and cloud practitioners looking to design lakehouse architectures and unify data governance across multiple query engines.
- Data scientists seeking to optimise data access and processing across diverse systems for advanced analytics and machine learning.
Prerequisites
- A laptop, to follow along with the lab exercise
Master Open Data Lake Architectures
One of the hottest trends in the data industry is the emergence of table formats such as Apache Iceberg, enabling the data layer of the analytics stack to be centralised between many engines. This offers great flexibility, but with some important trade-offs, particularly regarding federated governance and cataloging.
Join Snowflake, Slalom and AWS for an engaging half-day workshop where you’ll dive into the latest advancements in open data lake architectures. Learn how Snowflake’s Apache 2.0 OSS Iceberg catalog, Polaris, and other tools can help you unify data on S3 while offering federated access through various query engines such as Snowflake, Spark, Flink and Trino.
Anchoring on Financial Services, we’ll explore the motivations for unifying your data layer using Apache Iceberg, and dig deep into the practicalities of doing this today. We’ll close out the session by guiding you through a hands-on lab across Snowflake, Slalom and AWS so that you can test the concepts yourself!
What you’ll do:
- Explore the benefits and trade-offs of adopting the Iceberg table format
- Gain insights into Snowflake’s support for Iceberg and open-source standards through the Polaris Catalog project
- Understand the key challenges of designing an open lakehouse architecture with Snowflake, Slalom and AWS, focusing on unifying data governance and managing disparate data catalogs
- Learn about best practices to overcome these challenges
- Get hands-on experience building an open data lake using Snowflake and AWS Glue as engines on top of Iceberg data
Target Audience:
- Data engineers interested in leveraging Snowflake, Slalom and AWS to build scalable, open data lakehouse architectures.
- Data or enterprise architects and cloud practitioners looking to design lakehouse architectures and unify data governance across multiple query engines.
- Data scientists seeking to optimise data access and processing across diverse systems for advanced analytics and machine learning.
Prerequisites
- A laptop, to follow along with the lab exercise
