Remove Data Transformation Remove Machine Learning Remove Optimization
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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Enhance agility by localizing changes within business domains and clear data contracts. Eliminate centralized bottlenecks and complex data pipelines.

IoT 111
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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

Much has been written about struggles of deploying machine learning projects to production. As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. However, the concept is quite abstract.

IT 364
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Unparalleled Productivity: The Power of Cloudera Copilot for Cloudera Machine Learning

Cloudera

In the fast-evolving landscape of data science and machine learning, efficiency is not just desirable—it’s essential. Imagine a world where every data practitioner, from seasoned data scientists to budding developers, has an intelligent assistant at their fingertips.

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CIOs are rethinking how they use public cloud services. Here’s why.

CIO Business Intelligence

Expense optimization and clearly defined workload selection criteria will determine which go to the public cloud and which to private cloud, he says. Secure storage, together with data transformation, monitoring, auditing, and a compliance layer, increase the complexity of the system.

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The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure

DataKitchen

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

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An AI Chat Bot Wrote This Blog Post …

DataKitchen

ChatGPT> DataOps is a term that refers to the set of practices and tools that organizations use to improve the quality and speed of data analytics and machine learning. It involves bringing together people, processes, and technology to enable data-driven decision making and improve the efficiency of data-related workflows.

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12 data science certifications that will pay off

CIO Business Intelligence

The exam covers everything from fundamental to advanced data science concepts such as big data best practices, business strategies for data, building cross-organizational support, machine learning, natural language processing, scholastic modeling, and more.