https://powerbi.microsoft.com/en-us/blog/multivariate-reporting/Source: https://powerbi.microsoft.com/en-us/blog/multivariate-reporting/ What is Multivariate Reporting and when is it helpful? Multivariate Reporting (also known as Small Multiples) uses a series of visuals with the same measure and same scales but showcases various partitions of READ MORE
https://powerbi.microsoft.com/en-us/blog/how-to-do-multivariate-reporting-with-power-bi/Source: https://powerbi.microsoft.com/en-us/blog/how-to-do-multivariate-reporting-with-power-bi/ What is Multivariate Reporting and when is it helpful? Multivariate Reporting (also known as Small Multiples) uses a series of visuals with the same measure and same scales but showcases various partitions of READ MORE
Since announcing the release of our Jobs feature during the Azure IoT Central general availability launch, we are excited to share how we are working to improve your device management workflow through additional jobs functionalities. Today, you are now able to copy an existing job you’ve created, save a job to continue working on later, stop or resume a running job, and download a job details report once your job has completed running. These additional Jobs functionalities make managing your devices at scale much easier.
In order to copy a job you’ve created, simply select a job from your main jobs list and select “Copy”. This will open a copy of the job where you can optionally update any part of the job configuration. If any changes have been made to your device set since its creation, your copied job will reflect those changes for you to edit.
While you are editing your job, you now have the option to save the job to continue working on later by selecting “Save”. This saved job will appear on your main jobs list with a status of “Saved” and you can open it again at any time to continue editing.
Microsoft announced the general availability of Azure Data Lake Storage (ADLS) Gen2 and Azure Data Explorer in early February, which arms Azure with unmatched price performance and security as one of the best clouds for analytics. Azure Data Factory (ADF), is a fully-managed data integration service, that empowers you to copy data from over 80 data sources with a simple drag-and-drop experience and operationalize and manage the ETL/ELT flows with flexible control flow, rich monitoring, and continuous integration and continuous delivery (CI/CD) capabilities. In this blog post, we’re excited to update you on the latest integration in Azure Data Factory with ADLS Gen2 and Azure Data Explorer. You can now meet the advanced needs of your analytics workloads by leveraging these services.
Ingest and transform data with ADLS Gen2
Azure Data Lake Storage is a no-compromises data lake platform that combines the rich feature set of advanced data lake solutions with the economics, global scale, and enterprise grade security of Azure Blob Storage. Our recent post provides you with a comprehensive insider view on this powerful service.
Azure Data Factory supports ADLS Gen2 as a preview connector since ADLS Gen2 limited public preview. Now the connector has also reached general availability along
We recently shared the public preview of the Windows Virtual Desktop service on Azure. Now customers can access the only service that delivers simplified management, multi-session Windows 10, optimizations for Office 365 ProPlus, and support for Windows Server Remote Desktop Services (RDS) desktops and apps. With Windows Virtual Desktop, you can deploy and scale your Windows desktops and apps on Azure in minutes, while enjoying built-in security and compliance.
This means customers can now virtualize using multi-session Windows 10, Windows 7, and Windows Server desktops and apps (RDS) to Windows Virtual Desktop for a simplified management and deployment experience with Azure. We also built Windows Virtual Desktop as an extensible solution for our partners, including Citrix, Samsung, and Microsoft Cloud Solution Providers (CSP).
Access to Windows Virtual Desktop is available through applicable RDS and Windows Enterprise licenses. With the appropriate license, you just need to set up an Azure subscription to get started today. You can choose the type of virtual machines and storage you want to suit your environment. You can optimize costs by taking advantage of Reserved Instances with up to a 72 percent discount and using multi-session Windows 10.
You can read more detail about Windows
We’re excited to announce that Forrester has named Microsoft as a Leader in The Forrester Wave™: Big Data NoSQL, Q1 2019 based on their evaluation of Azure Cosmos DB. We believe Forrester’s findings validate the exceptional market momentum of Azure Cosmos DB and how happy our customers are with the product.
NoSQL platforms are on the rise
According to Forrester, “half of global data and analytics technology decision makers have either implemented or are implementing NoSQL platforms, taking advantage of the benefits of a flexible database that serves a broad range of use cases…While many organizations are complementing their relational databases with NoSQL, some have started to replace them to support improved performance, scale, and lower their database costs.”
Azure Cosmos DB has market momentum
Azure Cosmos DB is Microsoft’s globally distributed, multi-model database service for mission-critical workloads. Azure Cosmos DB provides turnkey global distribution with unlimited endpoint scalability, elastic scaling of throughput (at multiple granularities, e.g., database, key-space, tables and collections) and storage worldwide, single-digit millisecond latencies at the 99th percentile, five well-defined consistency models, and guaranteed high availability, all backed by the industry-leading comprehensive SLAs. Azure Cosmos DB automatically indexes all data without requiring developers to
Self-service is core to Infrastructure-as-a-Service (IaaS). Back in the virtualization days, you had to wait for someone to create a VLAN for you, carve out a LUN, and find space on a host. If Microsoft Azure ran that way, we would have needed to hire more and more admins as our cloud business grew.
Do it yourself
A different approach was required, which is why IaaS is important. Azure’s IaaS gives the owner of the subscription everything they need to create virtual machines (VMs) and other resources on their own, without involving an administrator. To learn more visit our documentation, “Introduction to Azure Virtual Machines” and “Introduction to Azure Stack virtual machines.”
Let me give you a few examples that show Azure and Azure Stack self-service management of VMs.
Creating a VM is as simple as going through a wizard. You can create the VM by specifying everything needed for the VM in the “Create virtual machine” blade. You can include the operating system image or marketplace template, the size (memory, CPUs, number of disks, and NICs), high availability, storage, networking, monitoring, and even in guest configuration.
Learn more by visiting the following resources:
As the manufacturing industry tackles some significant challenges including an aging workforce, compliance issues, and declining revenue, the Internet of Things (IoT) is helping reinvent factories and key processes. At the heart of this transformation journey is the design and use of IoT-enabled machines that help lead to reduced downtime, increased productivity, and optimized equipment performance.
Learn how you can apply insights from real-world use cases of IoT-enabled intelligent manufacturing when you attend the Manufacturing IoT webinar on March 28th. For additional hands-on, actionable insights around intelligent edge and intelligent cloud IoT solutions, join us on April 19th for the Houston Solution Builder Conference.
Using IoT solutions to move from a reactive to predictive model
In the past, factory managers often had no way of knowing when a machine might begin to perform poorly or completely shut down. When something went wrong, getting the equipment back up and running was often time consuming and based on trial-and-error troubleshooting. And for the company, any unplanned downtime meant slowed or halted production, resulting in lower productivity and higher costs.
The development of IoT-enabled machines with sensors allows companies to improve overall efficiency, performance, and profitability. Rockwell Automation found it time consuming
With ever-increasing data volume and latency requirements, GPUs have become an indispensable tool for doing machine learning (ML) at scale. This week, we are excited to announce two integrations that Microsoft and NVIDIA have built together to unlock industry-leading GPU acceleration for more developers and data scientists.
Azure Machine Learning service is the first major cloud ML service to integrate RAPIDS, an open source software library from NVIDIA that allows traditional machine learning practitioners to easily accelerate their pipelines with NVIDIA GPUs ONNX Runtime has integrated the NVIDIA TensorRT acceleration library, enabling deep learning practitioners to achieve lightning-fast inferencing regardless of their choice of framework.
These integrations build on an already-rich infusion of NVIDIA GPU technology on Azure to speed up the entire ML pipeline.
“NVIDIA and Microsoft are committed to accelerating the end-to-end data science pipeline for developers and data scientists regardless of their choice of framework,” says Kari Briski, Senior Director of Product Management for Accelerated Computing Software at NVIDIA. “By integrating NVIDIA TensorRT with ONNX Runtime and RAPIDS with Azure Machine Learning service, we’ve made it easier for machine learning practitioners to leverage NVIDIA GPUs across their data science workflows.”
Azure Machine Learning service integration with NVIDIA