Remove Data Architecture Remove Data Processing Remove Management Remove Metadata
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The Top Three Entangled Trends in Data Architectures: Data Mesh, Data Fabric, and Hybrid Architectures

Cloudera

Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. Data teams are confused as to whether they should get on the bandwagon of just one of these trends or pick a combination. First, we describe how data mesh and data fabric could be related.

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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

Over the years, data lakes on Amazon Simple Storage Service (Amazon S3) have become the default repository for enterprise data and are a common choice for a large set of users who query data for a variety of analytics and machine leaning use cases. Analytics use cases on data lakes are always evolving.

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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. The data can be reattached to UltraWarm when needed.

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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Ontotext

It enriched their understanding of the full spectrum of knowledge graph business applications and the technology partner ecosystem needed to turn data into a competitive advantage. Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

One important feature is to run different workloads such as business intelligence (BI), Machine Learning (ML), Data Science and data exploration, and Change Data Capture (CDC) of transactional data, without having to maintain multiple copies of data.

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Announcing Alation 4.0 with Alation Connect

Alation

Information about popular users of data is very important, as it provides knowledge from someone else, often outside of a consumer’s immediate network. For data stewards, this means answering: Where should I focus if there’s data to manage? How do I communicate semantic changes to consumers who rely on this data?

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How Cargotec uses metadata replication to enable cross-account data sharing

AWS Big Data

They chose AWS Glue as their preferred data integration tool due to its serverless nature, low maintenance, ability to control compute resources in advance, and scale when needed. To share the datasets, they needed a way to share access to the data and access to catalog metadata in the form of tables and views.