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Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

ElastiCache manages the real-time application data caching, allowing your customers to experience microsecond response times while supporting high-throughput handling of hundreds of millions of operations per second. In the inventory management and forecasting solution, AWS Glue is recommended for data transformation.

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

Specifically, the system uses Amazon SageMaker Processing jobs to process the data stored in the data lake, employing the AWS SDK for Pandas (previously known as AWS Wrangler) for various data transformation operations, including cleaning, normalization, and feature engineering.

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Use Snowflake with Amazon MWAA to orchestrate data pipelines

AWS Big Data

We also orchestrated the data pipeline using Amazon MWAA, which ran tasks related to data transformation as well as Snowflake queries. We used Secrets Manager to store Snowflake connection information and credentials and Amazon SNS to publish the data output for end consumption. Bosco Albuquerque is a Sr.

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Streamline AWS WAF log analysis with Apache Iceberg and Amazon Data Firehose

AWS Big Data

To optimize their security operations, organizations are adopting modern approaches that combine real-time monitoring with scalable data analytics. They are using data lake architectures and Apache Iceberg to efficiently process large volumes of security data while minimizing operational overhead.

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Stream real-time data into Apache Iceberg tables in Amazon S3 using Amazon Data Firehose

AWS Big Data

In Transform records , select Turn on data transformation. To learn more about using Amazon Data Firehose with Apache Iceberg, see the Firehose Developer Guide or try the Immersion day workshop. About the authors Diego Garcia Garcia is a Specialist SA Manager for Analytics at AWS. For Version select $LATEST.

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