Remove Analytics Remove Data Integration Remove Metadata
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Simplify data integration with AWS Glue and zero-ETL to Amazon SageMaker Lakehouse

AWS Big Data

With the growing emphasis on data, organizations are constantly seeking more efficient and agile ways to integrate their data, especially from a wide variety of applications. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

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Bridging the gap between mainframe data and hybrid cloud environments

CIO Business Intelligence

A high hurdle many enterprises have yet to overcome is accessing mainframe data via the cloud. Mainframes hold an enormous amount of critical and sensitive business data including transactional information, healthcare records, customer data, and inventory metrics.

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7 Benefits of Metadata Management

erwin

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

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RDF-Star: Metadata Complexity Simplified

Ontotext

To handle such scenarios you need a transalytical graph database – a database engine that can deal with both frequent updates (OLTP workload) as well as with graph analytics (OLAP). Not Every Graph is a Knowledge Graph: Schemas and Semantic Metadata Matter. Metadata about Relationships Come in Handy. Schemas are powerful.

Metadata 119
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Build a high-performance quant research platform with Apache Iceberg

AWS Big Data

Iceberg offers distinct advantages through its metadata layer over Parquet, such as improved data management, performance optimization, and integration with various query engines. Unlike direct Amazon S3 access, Iceberg supports these operations on petabyte-scale data lakes without requiring complex custom code.

Metadata 107
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Monitoring Apache Iceberg metadata layer using AWS Lambda, AWS Glue, and AWS CloudWatch

AWS Big Data

Data lakes provide a unified repository for organizations to store and use large volumes of data. This enables more informed decision-making and innovative insights through various analytics and machine learning applications. This ensures that each change is tracked and reversible, enhancing data governance and auditability.

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The next generation of Amazon SageMaker: The center for all your data, analytics, and AI

AWS Big Data

This week on the keynote stages at AWS re:Invent 2024, you heard from Matt Garman, CEO, AWS, and Swami Sivasubramanian, VP of AI and Data, AWS, speak about the next generation of Amazon SageMaker , the center for all of your data, analytics, and AI. The relationship between analytics and AI is rapidly evolving.