Remove Machine Learning Remove Metadata Remove Publishing Remove Unstructured Data
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The Future Is Hybrid Data, Embrace It

Cloudera

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 108
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The Future Is Hybrid Data, Embrace It

CIO Business Intelligence

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 97
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Ontotext’s Top 5 Most Popular Blog Posts for 2020

Ontotext

In its third generation, Ontotext Platform enables organizations to build, use and evolve knowledge graphs as a hub for data, metadata and content. The article also explains how enterprise knowledge graphs enable organizations to incorporate machine learning algorithms for the smart interpretation of their data.

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5 Types of Costly Data Waste and How to Avoid Them

CIO Business Intelligence

It isn’t practical to save all your data, but it is important to realize data may be valuable for other projects. You lose that add-on value when you throw data away. . This type of data waste results in missing out on the second project advantage. You have data but don’t use it.

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Ontotext Invents the Universe So You Don’t Need To

Ontotext

Content Enrichment and Metadata Management. The value of metadata for content providers is well-established. When that metadata is connected within a knowledge graph, a powerful mechanism for content enrichment is unlocked. The vast majority of that information is unstructured and unstructured means undiscoverable.

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

AWS Big Data

Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats. However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. He holds a PhD on data management in the cloud.

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The state of data quality in 2020

O'Reilly on Data

Comparatively few organizations have created dedicated data quality teams. Just 20% of organizations publish data provenance and data lineage. Adopting AI can help data quality. Almost half (48%) of respondents say they use data analysis, machine learning, or AI tools to address data quality issues.