SIBYL: A machine learning-based framework for forecasting dynamic workloads

SIBYL is a machine learning model that makes highly accurate predictions of database queries, enabling tuning for more efficiency. Applying traditional database optimizations to these predicted queries helps maintain high performance as demands change.

The post SIBYL: A machine learning-based framework for forecasting dynamic workloads appeared first on Microsoft Research.

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3 Microsoft marketing campaigns that can help position your AI-powered solutions​

The transformation to AI-based automation is a new reality for businesses worldwide. By 2025, it’s expected that 95% of all new digital workloads will deploy to the cloud and 90% of enterprise apps will use AI technology. As a Microsoft … Continue reading 3 Microsoft marketing campaigns that can help position your AI-powered solutions​

Part 6: Introducing Deployment Stacks to Azure Data Factory

Introduction
This is part 6 on our series on Azure Data Factory CI/CD. This section will cover how to incorporate Azure Deployment Stacks into your Azure DevOps Pipelines.
Part 1

Architecture and Scenario
Creating resources in Azure
Create Azure Stora… Continue reading Part 6: Introducing Deployment Stacks to Azure Data Factory

Boxfusion and Skypoint offer transactable partner solutions in Azure Marketplace

Microsoft partners like Boxfusion and Skypoint deliver transact-capable offers, which allow you to purchase directly from Azure Marketplace. Learn about these offers below:
 

Botsa: Botsa works with Microsoft Teams to provide a simple,&n… Continue reading Boxfusion and Skypoint offer transactable partner solutions in Azure Marketplace

How to budget your Azure cloud spend with Microsoft Cost Management

Introduction
If you are using Azure for your cloud applications, you might be wondering how to manage your costs effectively. You might have heard of Microsoft Cost Management, a service that helps you monitor, analyze, and optimize your cloud spending… Continue reading How to budget your Azure cloud spend with Microsoft Cost Management