Remove Dashboards Remove Data Transformation Remove Data Warehouse Remove Snapshot
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How SafetyCulture scales unpredictable dbt Cloud workloads in a cost-effective manner with Amazon Redshift

AWS Big Data

Amazon Redshift is a fully managed data warehouse service that tens of thousands of customers use to manage analytics at scale. Together with price-performance , Amazon Redshift enables you to use your data to acquire new insights for your business and customers while keeping costs low.

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How Tricentis unlocks insights across the software development lifecycle at speed and scale using Amazon Redshift

AWS Big Data

Initially, Tricentis defines these dashboards and charts to enable insight on test runs, test traceability with requirements, and many other pre-defined use cases that can be valuable to customers. As the files are created, another process is triggered to load the data from each customer on their schema or table on Amazon Redshift.

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Build incremental data pipelines to load transactional data changes using AWS DMS, Delta 2.0, and Amazon EMR Serverless

AWS Big Data

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 Let’s refer to this S3 bucket as the raw layer.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

If you ask an engineer to show how they operate the application in production, they will likely show containers and operational dashboards—not unlike any other software service. Data is at the core of any ML project, so data infrastructure is a foundational concern. Enter the software development layers. Versioning.

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