16

Oct

Power BI Report Server release timing update
Power BI Report Server release timing update

https://powerbi.microsoft.com/en-us/blog/power-bi-report-server-release-timing-update/Source: https://powerbi.microsoft.com/en-us/blog/power-bi-report-server-release-timing-update/           Power BI Report Server was first launched in June 2017 as our on-premises server product, giving customers the ability to adopt Power BI today while preserving their flexibility to move to the Power READ MORE

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16

Oct

Webinar 10/18 Group Program Manager, Josh Caplan, and the Power BI team host an Ask Anything around managing and monitoring Power BI Premium

https://powerbi.microsoft.com/en-us/blog/webinar-10-18-group-program-manager-josh-caplan-and-the-power-bi-team-host-an-ask-anything-around-managing-and-monitoring-power-bi-premium/Source: https://powerbi.microsoft.com/en-us/blog/webinar-10-18-group-program-manager-josh-caplan-and-the-power-bi-team-host-an-ask-anything-around-managing-and-monitoring-power-bi-premium/           This webinar is dedicated to answering your questions around monitoring and managing and Power BI Premium.

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16

Oct

SQL Server 2019 CTP 2.0 New Features – Introducing the Page Cracker (AKA sys.dm_db_page_info)!

https://blogs.msdn.microsoft.com/sql_server_team/sql-server-2019-ctp-2-0-new-features-introducing-the-page-cracker-aka-sys-dm_db_page_info/Source: https://blogs.msdn.microsoft.com/sql_server_team/sql-server-2019-ctp-2-0-new-features-introducing-the-page-cracker-aka-sys-dm_db_page_info/   Microsoft Ignite 2018 is fading away in the rearview mirror, but the excitement over all the new features and the vision shared there is just beginning. You’re probably seeing lots of buzz around the new Big Data READ MORE

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16

Oct

ONNX Runtime for inferencing machine learning models now in preview

We are excited to release the preview of ONNX Runtime, a high-performance inference engine for machine learning models in the Open Neural Network Exchange (ONNX) format. ONNX Runtime is compatible with ONNX version 1.2 and comes in Python packages that support both CPU and GPU to enable inferencing using Azure Machine Learning service and on any Linux machine running Ubuntu 16.

ONNX is an open source model format for deep learning and traditional machine learning. Since we launched ONNX in December 2017 it has gained support from more than 20 leading companies in the industry. ONNX gives data scientists and developers the freedom to choose the right framework for their task, as well as the confidence to run their models efficiently on a variety of platforms with the hardware of their choice.

The ONNX Runtime inference engine provides comprehensive coverage and support of all operators defined in ONNX. Developed with extensibility and performance in mind, it leverages a variety of custom accelerators based on platform and hardware selection to provide minimal compute latency and resource usage. Given the platform, hardware configuration, and operators defined within a model, ONNX Runtime can utilize the most efficient execution provider to deliver the

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16

Oct

Azure IoT Reference Architecture 2.1 release
Azure IoT Reference Architecture 2.1 release

A few months ago, we released a significant update to the Azure IoT Reference Architecture, a downloadable resource that aims to accelerate customers building IoT solutions on Azure by providing a proven production ready architecture and technology implementation choices.

Today, we are happy to release updated version 2.1 of the Azure IoT Reference Architecture. The document offers an overview of the IoT space, recommended subsystem factoring for scalable IoT solutions, prescriptive technology recommendations per subsystem, and detailed sections that explore use cases and technology alternatives.

This latest version of the guide includes four essential updates:

Guidance to build IoT solutions by leveraging SaaS (Azure IoT Central), PaaS (Azure IoT solution accelerators), or IaaS (using OSS stack). Azure IoT Central is a fully managed global IoT SaaS (software-as-a-service) solution that makes it easy to connect, monitor, and manage your IoT assets at scale. Azure IoT solution accelerators are open source offerings that provide end to end examples showcasing the use of Azure technologies to achieve faster time to market and time to value. Incorporating Azure IoT Edge as the intelligent edge for expanding the set of connected devices that gather telemetry, generate insights, and take action based on information close to

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16

Oct

Accessibility and array support with Azure Blockchain Workbench 1.4.0

We’ve been very grateful for the feedback you’ve given us since we first introduced Azure Blockchain Workbench in public preview a few months ago. Your feedback continues to be an essential and impactful part of our work. For this release, we focused on making Workbench more accessible for everyone. Accessibility is a key pillar in our vision of empowering every person and every organization to achieve more. We are excited to share some of the improvements we’ve made with accessibility in mind.

To use 1.4, you can either deploy a new instance of Workbench through the Azure Portal or upgrade your existing deployment to 1.4.0 using our upgrade script. This update includes the following improvements:

Better accessibility for screen readers and keyboard navigation

Azure Blockchain Workbench is far more than UI within client apps. Workbench provides a rich developer scaffold for you to develop and integrate blockchain solutions within your enterprise.

The Web client gives you an easy to use the environment to validate, test, and view blockchain applications. The application interface is dynamically generated based on smart contract metadata and can accommodate any use case. The client application delivers a user-facing front-end to the complete blockchain applications generated

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16

Oct

Accelerating AI in healthcare: Security, privacy, and compliance

Healthcare is drowning in data. Every patient brings a record that could span decades, with x-rays, MRIs, and other data that can affect every decision. Providers and payers bring their own collateral to the table. Skills, policies, and certifications are just the start. Complying with regulations such as the Health Insurance Portability and Accountability Act (HIPAA) present additional burdens on any process. But there is a remedy: AI (Artificial Intelligence) and ML (machine learning) are powerful tools that can change the way healthcare organizations deal with the tsunami of healthcare data.

Use cases where AI can help vary from diagnostic imaging to predicting the patient length of stay, and even chatbots. But these initiatives must avoid breaches, ransomware, and other privacy compliance issues.

Join this upcoming webinar live on October 18, 2018, at 11:00 AM Pacific Time, bringing you thought leaders from across the healthcare industry including:

Andrew Hicks, VP, Healthcare Assurance Services at Coalfire Mitch Parker, Executive Director, Information Security, and Compliance at IU Health David Houlding, Principal Healthcare lead at Microsoft

Each presenter will provide practical advice on how to address security, privacy, and compliance with AI solutions in healthcare.

Key takeaways: AI in healthcare trends and risks

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16

Oct

Apache Spark jobs gain up to 9x speed up with HDInsight IO Cache

Today, we are pleased to reveal the preview of HDInsight IO Cache, a new transparent data caching feature of Azure HDInsight that provides customers with up to a 9x performance improvement for Apache Spark jobs. We know from our customers that when it comes to analytics cost efficiency of managed cloud-based Apache Hadoop and Spark services is one of their major attractors. HDInsight IO Cache allows us to improve this key value proposition even further by improving performance without a corresponding increase in costs.

Architecture

Azure HDInsight is a cloud platform service for open source analytics that aims to bring the best open source projects and integrate them natively on Azure. There are many open source caching projects that exists in the ecosystem: Alluxio, Ignite, and RubiX to name a few prominent ones.

HDInsight IO Cache is based on RubiX. RubiX is one of the more recent projects and has a distinct architecture. Unlike other caching projects, it doesn’t reserve operating memory for caching purposes. Instead, it leverages recent advances in SSD technology to their fullest potential to make explicit memory management unnecessary. Modern SSDs routinely provide more than 1GB per second of bandwidth. Coupled with automatic operating system in-memory

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16

Oct

Aggregations for petabyte-scale BI available in the Power BI service

https://powerbi.microsoft.com/en-us/blog/aggregations-for-petabyte-scale-bi-available-in-the-power-bi-service/Source: https://powerbi.microsoft.com/en-us/blog/aggregations-for-petabyte-scale-bi-available-in-the-power-bi-service/          

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16

Oct

Azure Marketplace new offers – Volume 21

https://azure.microsoft.com/blog/azure-marketplace-new-offers-volume-21/We continue to expand the Azure Marketplace ecosystem. From September 1 to 15, 29 new offers successfully met the onboarding criteria and went live. See details of the new offers below: Virtual Machines Active Directory Certificate Services 2016 PKI: Quickly READ MORE

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