Remove Analytics Remove Data Processing Remove Metadata
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Accelerate your migration to Amazon OpenSearch Service with Reindexing-from-Snapshot

AWS Big Data

Each Lucene index (and, therefore, each OpenSearch shard) represents a completely independent search and storage capability hosted on a single machine. How RFS works OpenSearch and Elasticsearch snapshots are a directory tree that contains both data and metadata. The following is an example for the structure of an Elasticsearch 7.10

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Internally, making data accessible and fostering cross-departmental processing through advanced analytics and data science enhances information use and decision-making, leading to better resource allocation, reduced bottlenecks, and improved operational performance. Eliminate centralized bottlenecks and complex data pipelines.

IoT 101
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Modernize your legacy databases with AWS data lakes, Part 2: Build a data lake using AWS DMS data on Apache Iceberg

AWS Big Data

format(dbname, table_name)) except Exception as ex: print(ex) failed_table = {"table_name": table_name, "Reason": ex} unprocessed_tables.append(failed_table) def get_table_key(host, port, username, password, dbname): jdbc_url = "jdbc:sqlserver://{0}:{1};databaseName={2}".format(host, To start the job, choose Run. format(dbname)).config("spark.sql.catalog.glue_catalog.catalog-impl",

Data Lake 101
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Use Amazon Kinesis Data Streams to deliver real-time data to Amazon OpenSearch Service domains with Amazon OpenSearch Ingestion

AWS Big Data

You can use this approach for a variety of use cases, from real-time log analytics to integrating application messaging data for real-time search. This allows the log analytics pipeline to meet Well-Architected best practices for resilience ( REL04-BP02 ) and cost ( COST09-BP02 ).

Metadata 109
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Demystify data sharing and collaboration patterns on AWS: Choosing the right tool for the job

AWS Big Data

Let’s briefly describe the capabilities of the AWS services we referred above: AWS Glue is a fully managed, serverless, and scalable extract, transform, and load (ETL) service that simplifies the process of discovering, preparing, and loading data for analytics. Amazon Athena is used to query, and explore the data.

Sales 105
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How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

These nodes can implement analytical platforms like data lake houses, data warehouses, or data marts, all united by producing data products. The Institutional Data & AI platform adopts a federated approach to data while centralizing the metadata to facilitate simpler discovery and sharing of data products.

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Integrate custom applications with AWS Lake Formation – Part 2

AWS Big Data

Add Amplify hosting Amplify can host applications using either the Amplify console or Amazon CloudFront and Amazon Simple Storage Service (Amazon S3) with the option to have manual or continuous deployment. For simplicity, we use the Hosting with Amplify Console and Manual Deployment options.