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Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt

AWS Big Data

Some important considerations: For implementing dbt modeling on Athena, refer to the dbt-on-aws / athena GitHub repository for experimentation For implementing dbt modeling on Amazon Redshift, refer to the dbt-on-aws / redshift GitHub repository for experimentation.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

ML apps need to be developed through cycles of experimentation: due to the constant exposure to data, we don’t learn the behavior of ML apps through logical reasoning but through empirical observation. Besides infrastructure, effective A/B testing requires a control plane, a modern experimentation platform, such as StatSig. Versioning.

IT 364
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Apply Modern CRM Dashboards & Reports Into Your Business – Examples & Templates

datapine

Additionally, CRM dashboard tools provide access to insights that offer a concise snapshot of your customer-driven performance and activities through a range of features and functionalities empowered by online data visualization tools. Your Chance: Want to build professional CRM reports & dashboards?

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Backtesting index rebalancing arbitrage with Amazon EMR and Apache Iceberg

AWS Big Data

Iceberg tags – The Iceberg branching and tagging feature allows users to tag specific snapshots of their data tables with meaningful labels using SQL syntax or the Iceberg library, which correspond to specific events notable to internal investment teams. Tag this data to preserve a snapshot of it. Configure a Spark session.

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How Gupshup built their multi-tenant messaging analytics platform on Amazon Redshift

AWS Big Data

E.g., use the snapshot-restore feature to quickly create a green experimental cluster from an existing blue serving cluster. By combining Redshift’s scalability, snapshots, workload management, and low-operational approach, Gupshup provides data-driven insights in less than 15 minutes analytics refresh rate.

Analytics 119
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Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes

AWS Big Data

The following examples are also available in the sample notebook in the aws-samples GitHub repo for quick experimentation. In that case, we have to query the table with the snapshot-id corresponding to the deleted row. We expire the old snapshots from the table and keep only the last two.

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Build a multi-Region and highly resilient modern data architecture using AWS Glue and AWS Lake Formation

AWS Big Data

The utility for cloning and experimentation is available in the open-sourced GitHub repository. The on-demand mode is a batch replication that takes a snapshot of the metadata at a specific point in time and uses it to synchronize the metadata. These mechanisms can be customized for your organization’s processes.