Remove Data Lake Remove Data Processing Remove Recreation/Entertainment
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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

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Get Your Analytics Insights Instantly – Without Abandoning Central IT

Cloudera

Cloudera’s Data Warehouse service allows raw data to be stored in the cloud storage of your choice (S3, ADLSg2). It will be stored in your own namespace, and not force you to move data into someone else’s proprietary file formats or hosted storage. Proprietary file formats mean no one else is invited in! Separate compute.

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Real-time streaming data top picks you cannot miss at AWS re:Invent 2023

AWS Big Data

With real-time streaming data, organizations can reimagine what’s possible. From enabling predictive maintenance in manufacturing to delivering hyper-personalized content in the media and entertainment industry, and from real-time fraud detection in finance to precision agriculture in farming, the potential applications are vast.

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How Amazon Finance Automation built a data mesh to support distributed data ownership and centralize governance

AWS Big Data

The workflow contains the following steps: Data is saved by the producer in their own Amazon Simple Storage Service (Amazon S3) buckets. Data source locations hosted by the producer are created within the producer’s AWS Glue Data Catalog. Data source locations are registered with Lake Formation.

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Implement disaster recovery with Amazon Redshift

AWS Big Data

Set up a custom domain with Amazon Redshift in the primary Region In the hosted zone that Route 53 created when you registered the domain, create records to tell Route 53 how you want to route traffic to Redshift endpoint by completing the following steps: On the Route 53 console, choose Hosted zones in the navigation pane.

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Extreme data center pressure? Burst to the cloud with CDP!

Cloudera

Inability to maintain context – This is the worst of them all because every time a data set or workload is re-used, you must recreate its context including security, metadata, and governance. Cloud deployments add tremendous overhead because you must reimplement security measures and then manage, audit, and control them.