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Simplifying Data Architecture and Security to Accelerate Value

Snowflake

Snowflake is committed to doing just that by continually adding features to help our customers simplify how they architect their data infrastructure. At BUILD 2024, we announced several enhancements and innovations designed to help you build and manage your data architecture on your terms. Here’s a closer look.

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2024 Governance Trends for Data Leaders

phData: Data Engineering

In an effort to better understand where data governance is heading, we spoke with top executives from IT, healthcare, and finance to hear their thoughts on the biggest trends, key challenges, and what insights they would recommend. With that, let’s get into the governance trends for data leaders! No problem!

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Data Fabric: The Future of Data Architecture

Monte Carlo

Today, as data sources become increasingly varied, data management becomes more complex, and agility and scalability become essential traits for data leaders, data fabric is quickly becoming the future of data architecture. If data fabric is the future, how can you get your organization up-to-speed?

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Data Fabric: The Future of Data Architecture

Monte Carlo

Today, as data sources become increasingly varied, data management becomes more complex, and agility and scalability become essential traits for data leaders, data fabric is quickly becoming the future of data architecture. If data fabric is the future, how can you get your organization up-to-speed?

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

Cloudera

It supports business objectives like increasing revenues, improving customer experience, and driving profitability by giving business units and users access to relevant data so they can quickly gain the insight they need. This does not mean ‘one of each’ – a public cloud data strategy and an on-prem data strategy.

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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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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. Let’s dive deeper.

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