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Accelerate HiveQL with Oozie to Spark SQL migration on Amazon EMR

AWS Big Data

We split the solution into two primary components: generating Spark job metadata and running the SQL on Amazon EMR. The first component (metadata setup) consumes existing Hive job configurations and generates metadata such as number of parameters, number of actions (steps), and file formats. X Python 3.8 Amazon EMR 6.1

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. We keep feeding the monster data.

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Federate Amazon QuickSight access with open-source identity provider Keycloak

AWS Big Data

Download the SAML metadata file. In the navigation pane under Clients , import the SAML metadata file. Download the Keycloak IdP SAML metadata file from that URL location. For Metadata document , upload the Keycloak IdP SAML metadata XML file you downloaded and saved to your local machine earlier. Choose Browse.

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Why We Started the Data Intelligence Project

Alation

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

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Generate security insights from Amazon Security Lake data using Amazon OpenSearch Ingestion

AWS Big Data

Optionally, specify the Amazon S3 storage class for the data in Amazon Security Lake. For more information, refer to Lifecycle management in Security Lake. Review the details and create the data lake. Choose Next. Additionally, the principal must have permission to pass the pipeline role to OpenSearch Ingestion.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

I mention this here because there was a lot of overlap between current industry data governance needs and what the scientific community is working toward for scholarly infrastructure. The gist is, leveraging metadata about research datasets, projects, publications, etc., Or something. Nothing Spreads Like Fear”.