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Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

AWS Big Data

They recognize the importance of accurate, complete, and timely data in enabling informed decision-making and fostering trust in their analytics and reporting processes. By selecting the corresponding asset, you can understand its content through the readme, glossary terms , and technical and business metadata.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

The Data Catalog provides metadata that allows analytics applications using Athena to find, read, and process the location data stored in Amazon S3. You can test this solution yourself using the AWS Samples GitHub repository. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

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How SumUp made digital analytics more accessible using AWS Glue

AWS Big Data

Founded in 2012, SumUp is the financial partner for more than 4 million small merchants in over 35 markets worldwide, helping them start, run and grow their business. Data Catalog: We also wanted to automate a Glue Crawler to have metadata in a Data Catalog and be able to explore our files in S3 with Athena.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Not that I’m implying anything about current economic conditions vis-a-vis the timing of this report… #justsayin. Allows metadata repositories to share and exchange.

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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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Build efficient ETL pipelines with AWS Step Functions distributed map and redrive feature

AWS Big Data

Amazon S3 hosts the metadata of all the tables as a.csv file. The pipeline uses the Step Functions distributed map to read the table metadata from Amazon S3, iterate on every single item, and call the downstream AWS Glue job in parallel to export the data. The following diagram illustrates the Step Functions workflow.

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Best practices to implement near-real-time analytics using Amazon Redshift Streaming Ingestion with Amazon MSK

AWS Big Data

ORDERTOPIC" WHERE CAN_JSON_PARSE(kafka_value); The metadata column kafka_value that arrives from Amazon MSK is stored in VARBYTE format in Amazon Redshift. To avoid these types of issues, test the logic of your materialized view definition carefully; otherwise, land the records into the default VARBYTE column and process them later.