Remove Data Processing Remove Publishing Remove Structured Data Remove Unstructured Data
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Reflections on the Knowledge Graph Conference 2023

Ontotext

The event attracts individuals interested in graph technology, machine learning and natural language processes in numerous verticals, including publishing, government, financial services, manufacturing and retail. This message resonates with the market positioning of Ontotext as a trusted, stable option for demanding data-centric use cases.

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How to Take Back 40-60% of Your IT Spend by Fixing Your Data

Ontotext

The pathway forward doesn’t require ripping everything out but building a semantic “graph” layer across data to connect the dots and restore context. However, it will take effort to formalize a shared semantic model that can be mapped to data assets, and turn unstructured data into a format that can be mined for insight.

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The new challenges of scale: What it takes to go from PB to EB data scale

CIO Business Intelligence

How is it possible to manage the data lifecycle, especially for extremely large volumes of unstructured data? Unlike structured data, which is organized into predefined fields and tables, unstructured data does not have a well-defined schema or structure.

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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”.

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