Remove Analytics Remove Metadata Remove Publishing Remove Unstructured Data
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Do I Need a Data Catalog?

erwin

The data catalog is a searchable asset that enables all data – including even formerly siloed tribal knowledge – to be cataloged and more quickly exposed to users for analysis. Three Types of Metadata in a Data Catalog. Technical Metadata. Operational Metadata. for analysis and integration purposes).

Metadata 132
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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 110
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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. But this is not your grandfather’s big data.

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. From Data Silos to Data Fabric with Knowledge Graphs. GraphDB Empowers Scientific Projects to Fight COVID-19 and Publish Knowledge Graphs.

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Ontotext Invents the Universe So You Don’t Need To

Ontotext

Ontotext is also on the list of vendors supporting knowledge graph capabilities in their “2021 Planning Guide for Data Analytics and Artificial Intelligence” report. Content Enrichment and Metadata Management. The value of metadata for content providers is well-established. Developer-Friendly Semantic Technology.

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

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 106
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Modernize Using The BI & Analytics Magic Quadrant

Rita Sallam

And here we are now, past the tipping point of a more than 10 to 11 year transition away from IT-centric reporting platforms to modern BI and analytics platforms that make up much of the new buying in the BI and Analytics market. A modern BI platform supports IT-enabled analytic content development. Moving to Modern.