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Artificial Intelligence in Cloud Computing

Scalegrid

Exploring artificial intelligence in cloud computing reveals a game-changing synergy. Predictive analytics, powered by AI, enhance business processes and optimize resource allocation according to workload demands. Key among these trends is the emphasis on security and intelligent analytics.

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AWS re:Invent 2023 guide: Generative AI takes a front seat

Dynatrace

At the AWS re:Invent 2023 conference, generative AI is a centerpiece. In this AWS re:Invent 2023 guide, we explore the role of generative AI in the issues organizations face as they move to the cloud: IT automation, cloud migration and digital transformation, application security, and more.

AWS 210
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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes.

Analytics 209
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AWS Re:Invent 2021 guide: Multicloud modernization and digital transformation

Dynatrace

Digital transformation with AWS: Making it real with AIOps. When Amazon launched AWS Lambda in 2014, it ushered in a new era of serverless computing. Amazon Web Services (AWS) and other cloud platforms provide visibility into their own systems, but they leave a gap concerning other clouds, technologies, and on-prem resources.

AWS 228
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. Let’s walk through the top use cases for Greenplum: Analytics.

Big Data 321
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

This approach enables organizations to use this data to build artificial intelligence (AI) and machine learning models from large volumes of disparate data sets. The result is a framework that offers a single source of truth and enables companies to make the most of advanced analytics capabilities simultaneously. Query language.

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Enhance data management with Grail: Ultimate guide to custom buckets and security policies

Dynatrace

Grail: Enterprise-ready data lakehouse Grail, the Dynatrace causational data lakehouse, was explicitly designed for observability and security data, with artificial intelligence integrated into its foundation. Another example would be a business unit admin who needs to have access to departmental data across buckets.