Remove Data Architecture Remove Data Management Remove Unstructured Data
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Simplifying Data Architecture and Security to Accelerate Value

Snowflake

At BUILD 2024, we announced several enhancements and innovations designed to help you build and manage your data architecture on your terms. Ingest data more efficiently and manage costs For data managed by Snowflake, we are introducing features that help you access data easily and cost-effectively.

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Data Fabric: The Future of Data Architecture

Monte Carlo

Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.

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Data Fabric: The Future of Data Architecture

Monte Carlo

Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.

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Driving Success With a Modern Data Architecture and a Hybrid Approach in the Financial Services and Telco Industries

Cloudera

The next step will be for telecom operators to continue tapping into these customer-centric data sources to develop novel ways of meeting customer needs that ultimately translate to an improved overall experience. This does not mean ‘one of each’ – a public cloud data strategy and an on-prem data strategy.

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What Separates Hybrid Cloud and ‘True’ Hybrid Cloud?

Cloudera

To attain that level of data quality, a majority of business and IT leaders have opted to take a hybrid approach to data management, moving data between cloud, on-premises -or a combination of the two – to where they can best use it for analytics or feeding AI models. Data comes in many forms.

Cloud 97
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What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools

Monte Carlo

Key Differences Between AI Data Engineers and Traditional Data Engineers While traditional data engineers and AI data engineers have similar responsibilities, they ultimately differ in where they focus their efforts. Let’s examine a few.

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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 111