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Google BigQuery Architecture for Data Engineers

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Google’s BigQuery is an enterprise-grade cloud-native data warehouse. BigQuery was first launched as a service in 2010, with general availability in November 2011.

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The Future Is Hybrid Data, Embrace It

Cloudera

We live in a hybrid data world. 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 112
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The Future Is Hybrid Data, Embrace It

CIO Business Intelligence

We live in a hybrid data world. 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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The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Ontotext

If you’ve used Google, you’ve used the cornucopia of Linked data across the Web, through Google’s Knowledge Graph (Google’s Knowledge Graph is reportedly supported by Freebase – the knowledge acquired by Google in 2010. ) Below, we outline the two directions in which we at Ontotext see and build the Semantic Web.

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NVMe vs. SATA: What’s the difference?

IBM Big Data Hub

Unlike magnetic storage (such as HDDs and floppy drives) that store data using magnets, solid-state storage drives use NAND chips, a non-volatile storage technology that doesn’t require a power source to maintain its data. What is NVMe?

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Cloudera + Hortonworks, from the Edge to AI

Cloudera

They, too, saw the enormous potential for data at scale in the enterprise. Since 2011, our two companies have each innovated to build better products and win more business. In the competitive world of data management, we can each look with respect at the success of the other. We have each innovated separately in those areas.

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Themes and Conferences per Pacoid, Episode 7

Domino Data Lab

There are essentially four types encountered: image/video, audio, text, and structured data. That’s most likely a mix of devops, telematics, IoT, process control, and so on, although it has positive connotations for the adoption of reinforcement learning as well.