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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

We need robust versioning for data, models, code, and preferably even the internal state of applications—think Git on steroids to answer inevitable questions: What changed? The applications must be integrated to the surrounding business systems so ideas can be tested and validated in the real world in a controlled manner. Versioning.

IT 360
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Run Apache XTable in AWS Lambda for background conversion of open table formats

AWS Big Data

This post was co-written with Dipankar Mazumdar, Staff Data Engineering Advocate with AWS Partner OneHouse. Data architecture has evolved significantly to handle growing data volumes and diverse workloads. In case you don’t have sample data available for testing, we provide scripts for generating sample datasets on GitHub.

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Evaluating sample Amazon Redshift data sharing architecture using Redshift Test Drive and advanced SQL analysis

AWS Big Data

With the launch of Amazon Redshift Serverless and the various provisioned instance deployment options , customers are looking for tools that help them determine the most optimal data warehouse configuration to support their Amazon Redshift workloads. The following image shows the process flow.

Testing 111
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Open Data Lakehouse powered by Iceberg for all your Data Warehouse needs

Cloudera

Cloudera Contributors: Ayush Saxena, Tamas Mate, Simhadri Govindappa Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), we are excited to see customers testing their analytic workloads on Iceberg. We will publish follow up blogs for other data services. ID, TBL_ICEBERG_PART_2.NAME,

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

AWS Big Data

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Amazon Redshift RA3 with managed storage is the newest instance type for Provisioned clusters.

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Implement disaster recovery with Amazon Redshift

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. Document the entire disaster recovery process.

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Implement data warehousing solution using dbt on Amazon Redshift

AWS Big Data

dbt (DataBuildTool) offers this mechanism by introducing a well-structured framework for data analysis, transformation and orchestration. It also applies general software engineering principles like integrating with git repositories, setting up DRYer code, adding functional test cases, and including external libraries.

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