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Learn more about how University of Miami gained flexibility and DR resiliency with Azure VMware Solution
Azure Sentinel is a next-generation, cloud native SIEM that re-imagines, threat detection, investigation and response powered by the limitless speed and scale of the Azure Cloud and the advance services Azure delivers including AI, Automation and ease of deployment.
Security Operations teams use Azure Sentinel to generate detections as well as investigate and remediate threats. Offering your data, detections, automation, analysis and packaged expertise, to customers via integration with Azure Sentinel enables security teams with the right information at the right time to execute informed security responses.
Azure Sentinel Solutions make it easier than ever for joint customers to discover, deploy, and maximize the value of the partner integrations that you create.
This guidance will help you unlock more value for your current customers and create new use cases, reach new customers, and productize your integration investments.
This article includes
- Mutual Scenarios and how to decide which make sense.
- What technical features are needed to enable each scenario.
- Where to go for instructions on building and publishing
- What Microsoft programs can help you with getting to customers.
Microsoft has a large ecosystem of partners who specialize in mainframe migration tools and services to transform your mainframe workloads to Azure.
Read about the real impact and benefits businesses are experiencing by building AI solutions using Azure Machine Learning. The Forrester Consulting Total Economic Impact™ (TEI) study, comissioned by Microsoft, examines the potential return on investment (ROI) enterprises may realize with Azure Machine Learning.
Forrester interviewed five customers with experience using Azure ML and surveyed 199 data science, ML, or AI decision makers. For the purposes of this study, Forrester aggregated the results from these customers into a single composite organization to highlight:
- Projected return on investment (ROI) of 189% to 335%
- Projected net present value (NPV) of $2.3M to $4.0M
- Improved data scientist productivity by up to 25% and data engineering productivity by up to 40%
- Reduction in time to onboard new data scientists by 55%
- Streamlined model development, training, validation, and deployment
- Operationalized model explainability and monitoring
- Increased time-to-value of ML initiatives, improved model accuracy and increased revenue from ML insights
Ransomware and extortion are a high profit, low-cost business which has a debilitating impact on targeted organizations, national security, economic security, and public health and safety. What started as simple single-PC ransomware has grown to include a variety of extortion techniques directed at all types of corporate networks and cloud platforms.
To ensure customers running on Azure are protected against ransomware attacks, Microsoft has invested heavily on the security of our cloud platforms and has provided you the security controls you need to protect your Azure cloud workloads.
By leveraging Azure native ransomware protections and implementing the best practices recommended in this eBook, you are taking measures that ensures your organization is optimally positioned to prevent, protect and detect potential ransomware attacks on your Azure assets.
This eBook lays out key Azure native capabilities and defenses for ransomware attacks and guidance on how to proactively leverage these to protect your assets on Azure cloud.
Find out how to secure your Azure Virtual Desktop environment when migrating your virtual desktop infrastructure (VDI) to Azure. Read this security handbook to get technical hands-on guidance on how to help protect your apps and data in your Azure Virtual Desktop deployment.
Download the handbook to:
- Familiarize yourself with Azure Virtual Desktop architecture.
- Understand which Microsoft tools and Azure security services are automatically configured and which are your responsibility.
- Implement appropriate security measures for your organization’s data, apps, user identities, session hosts, and network access.
- Learn best practices for using Azure Security Center and improving your Azure Secure Score.
Learn how to save money, increase operational efficiency, and improve business agility by migrating to Azure Database for MySQL. Read this report from the Enterprise Strategy Group (ESG) to see how organizations can realize significant cost savings and benefits by moving their MySQL workloads to Azure Database for MySQL.
Read ESG’s analysis on how Azure Database for MySQL can:
- Save up to 48% when migrating on-premises workloads to Azure Database for MySQL.
- Reduce 93% of operational overhead by freeing up development capacity and administration costs.
- Increase revenue by $15.5 million as a result of shortening release times and delivering cloud-ready applications.
Get the report to learn more about ESG’s findings—and how to put them to work for your organization.
SQL Server has been around for a long time and is used to unlock data insights for organizations all over the world. For many IT professionals, SQL Server is at the core of their career in analytics, and they look to build upon their experience as their organization modernizes to the cloud.
Read the complimentary e-book Azure Synapse for the SQL Server Professional to learn how you can extend your existing SQL Server skillsets into Azure Synapse Analytics. Discover how to create business value and accelerate time-to-insight on a unified cloud-scale analytics platform.
Learn how to augment your SQL Server experience with Azure Synapse by:
- Building code-free ETL/ELT processes for data integration
- Exploring and experimenting with big data on your data lake
- Creating self-service business intelligence from mission-critical data warehousing workloads
Customers leverage Azure Databricks for Industrial IoT Analytics
Trying to start an AI or ML project can be a daunting task—particularly at the scale of an enterprise organization. Focusing on security, execution, and responsibility is imperative to realizing a successful ML project without ballooning costs or taking on unnecessary risk.
Microsoft is committed to helping enterprise organizations realize their AI and ML goals at scale. Azure Machine Learning is built on our own best practices developed through years of experimentation to help you get started quickly and accelerate your time to market with all of the tools and controls that make it easier to keep costs low and protect against risk. To
learn more, download this paper and visit the Machine Learning practitioners page at http://aka.ms/data-scientists.