Remove Data Processing Remove Metadata Remove Structured Data
article thumbnail

How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

An extract, transform, and load (ETL) process using AWS Glue is triggered once a day to extract the required data and transform it into the required format and quality, following the data product principle of data mesh architectures. From here, the metadata is published to Amazon DataZone by using AWS Glue Data Catalog.

IoT 100
article thumbnail

Have we reached the end of ‘too expensive’ for enterprise software?

CIO Business Intelligence

Content management systems: Content editors can search for assets or content using descriptive language without relying on extensive tagging or metadata. Intelligent data and content analysis Sentiment analysis Lets look at a practical example: an internal system allows employees to post short status messages about their work.

Software 128
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Implement a custom subscription workflow for unmanaged Amazon S3 assets published with Amazon DataZone

AWS Big Data

Amazon DataZone , a data management service, helps you catalog, discover, share, and govern data stored across AWS, on-premises systems, and third-party sources. After you create the asset, you can add glossaries or metadata forms, but its not necessary for this post. Delete the S3 bucket that hosted the unstructured asset.

article thumbnail

How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 124
article thumbnail

How ZS built a clinical knowledge repository for semantic search using Amazon OpenSearch Service and Amazon Neptune

AWS Big Data

We use leading-edge analytics, data, and science to help clients make intelligent decisions. We developed and host several applications for our customers on Amazon Web Services (AWS). These embeddings, along with metadata such as the document ID and page number, are stored in OpenSearch Service.

article thumbnail

From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

The Data Fabric paradigm combines design principles and methodologies for building efficient, flexible and reliable data management ecosystems. Knowledge Graphs are the Warp and Weft of a Data Fabric. To implement any Data Fabric approach, it is essential to be able to understand the context of data.

article thumbnail

Do Large Language Models Dream of Knowledge Graphs – Impressions from Day 2 At SEMANTiCS 2023

Ontotext

LLMs] call into question a fundamental tenet of Data Management: that in order to address non-trivial information needs, the first step is to explicitly structure data in order to lift them from the ambiguous swamp of our human language. Thankfully, lt-innovate.org already did a concise wrap-up.