Remove Data Quality Remove Metadata Remove Publishing Remove Structured Data
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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.

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Success Stories: Applications and Benefits of Knowledge Graphs in Financial Services

Ontotext

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. There are four groups of data that are naturally siloed: Structured data (e.g.,

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You Cannot Get to the Moon on a Bike!

Ontotext

Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. In order to integrate structured data, enterprises need to implement the data fabric pattern.

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The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Ontotext

The second one is the Linked Open Data (LOD): a cloud of interlinked structured datasets published without centralized control across thousands of servers. There are more than 80 million pages with semantic, machine interpretable metadata , according to the Schema.org standard. Take this restaurant, for example.

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The Enduring Significance of Data Modeling in the Modern Data-Driven Enterprise

erwin

Let’s explore the continued relevance of data modeling and its journey through history, challenges faced, adaptations made, and its pivotal role in the new age of data platforms, AI, and democratized data access. Embracing the future In the dynamic world of data, data modeling remains an indispensable tool.