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Data Warehouse Migration: How to Make This Strategic Move

Octopai

Migrating a data fulfillment center (i.e. warehouse). Your data warehouse is not too different from an Amazon fulfillment center. No one wants to disrupt this level of complexity in order to recreate it elsewhere. Your old data warehouse has become deprecated. Ready to take on the job?

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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 107
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Using DataOps to Drive Agility and Business Value

DataKitchen

Previously we would have a very laborious data warehouse or data mart initiative and it may take a very long time and have a large price tag. Jim Tyo added that in the financial services world, agility is critical. We had to go find someone who’s willing to open their mind for five minutes to an alternative reality.

Metrics 211
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Putting the Business Back Into Business Innovation

Timo Elliott

Most innovation platforms make you rip the data out of your existing applications and move it to some another environment—a data warehouse, or data lake, or data lake house or data cloud—before you can do any innovation. But that’s like ripping a tree out of the forest and trying to get it to grow elsewhere.

Data Lake 105
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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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How to Use Apache Iceberg in CDP’s Open Lakehouse

Cloudera

The general availability covers Iceberg running within some of the key data services in CDP, including Cloudera Data Warehouse ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Cloudera Data Engineering (Spark 3) with Airflow enabled. Cloudera Machine Learning .

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Implement model versioning with Amazon Redshift ML

AWS Big Data

We do this by dropping the original version of the model and recreating a model using the BYOM technique. He has more than 25 years of experience implementing large-scale data warehouse solutions. He is passionate about helping customers through their cloud journey and using the power of ML within their data warehouse.

Modeling 110