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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

In this post, we show you how you can convert existing data in an Amazon S3 data lake in Apache Parquet format to Apache Iceberg format to support transactions on the data using Jupyter Notebook based interactive sessions over AWS Glue 4.0. AWS Command Line Interface (AWS CLI) configured to interact with AWS Services. Choose ETL Jobs.

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Find the best Amazon Redshift configuration for your workload using Redshift Test Drive

AWS Big Data

Redshift Test Drive also provides additional features such as a self-hosted analysis UI and the ability to replicate external objects that a Redshift workload may interact with. Compare replay performance Redshift Test Drive also provides the ability to compare the replay runs visually using a self-hosted UI tool.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

The transformed zone is an enterprise-wide zone to host cleaned and transformed data in order to serve multiple teams and use cases. With Iceberg, ingestion, update, and querying processes can benefit from atomicity, snapshot isolation, and managing concurrency to keep a consistent view of data.

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Maximize the power of your lines of defense against cyber-attacks with IBM Storage FlashSystem and IBM Storage Defender

IBM Big Data Hub

In 2023, the FBI received a record number of 880,418 complaints with potential losses exceeding USD 12.5 When a cyberattack strikes, the ransomware code gathers information about target networks and key resources such as databases, critical files, snapshots and backups. Today, cybercrime is good business.

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