10

Jul

Power BI Service and Mobile June Feature Summary
Power BI Service and Mobile June Feature Summary

https://powerbi.microsoft.com/en-us/blog/power-bi-service-and-mobile-june-2018-feature-summary/Source: https://powerbi.microsoft.com/en-us/blog/power-bi-service-and-mobile-june-2018-feature-summary/           The month of June flew by quickly for Power BI. With summer in the air and MBAS just around the corner, we are laser focused on planning another unforgettable conference for you in READ MORE

10

Jul

How to use Siamese Network and Pre-trained CNNs for Fashion Similarity Matching

This post is co-authored by Erika Menezes, Software Engineer at Microsoft, and Chaitanya Kanitkar, Software Engineer at Twitter. This project was completed as part of the coursework for Stanford’s CS231n in Spring 2018.

Ever seen someone wearing an interesting outfit and wonder where you could buy it yourself?

You’re not alone – retailers world over are trying to capitalize on something very similar. Each time a fashion blogger posts a picture on Instagram or another photo-sharing site, it’s a low-cost sales opportunity. As online shopping and photo-sharing become ever more widely used, the use of user generated content (UGC) in marketing strategies has become pivotal in driving traffic and increasing sales for retailers. A key value proposition for UGC content such as images and videos is their authenticity when compared to professional content. However, this is also why working with UGC content can be more difficult as there is much less control over how the content looks or how it was generated.

Microsoft has been using deep learning for e-commerce visual search and inventory management using content-based image retrieval. Both efforts demonstrate solutions for the in-shop clothes retrieval task, where the query image and target catalog image are taken

10

Jul

Azure HDInsight now supports Apache Spark 2.3

Apache Spark 2.3.0 is now available for production use on the managed big data service Azure HDInsight. Ranging from bug fixes (more than 1400 tickets were fixed in this release) to new experimental features, Apache Spark 2.3.0 brings advancements and polish to all areas of its unified data platform.

Data engineers relying on Python UDFs get 10 times to a 100 times more speed, thanks to revamped object serialization between Spark runtime and Python. Data Scientist will be delighted by better integration of Deep Learning frameworks like TensorFlow with Spark Machine Learning pipelines. Business Analysts will find liberating availability of fast vectorized reader for ORC file format which finally makes interactive analytics in Spark practical over this popular columnar data format. Developers building real-time applications may be interested in experimenting with new Continuous Processing mode in Spark Structured Streaming which brings event processing latency to millisecond level.

Vectorized object serialization in Python UDFs

It is worth mentioning that PySpark is already fast and takes advantage of the vectorized data processing in core Spark engine as long as you are using DataFrame APIs. This is good news as it represents majority of the use cases if you follow best practices for

10

Jul

Streaming analytics use cases with Spark on Azure
Streaming analytics use cases with Spark on Azure

Sensors, IoT devices, social networks, and online transactions are all generating data that needs to be monitored constantly and acted on quickly. As a result, the need for large-scale, real-time stream processing is more evident now than ever before.

With Azure Databricks running on top of Spark, Spark Streaming enables data scientists and data engineers with powerful interactive and analytical applications across both streaming and historical data, while inheriting Spark’s ease of use and fault tolerance characteristics. Azure Databricks readily integrates with a wide variety of popular data sources, including HDFS, Flume, Kafka, and Twitter.

There are four main use cases Spark Streaming is being used today:

Streaming ETL — Data is continuously cleaned and aggregated before being pushed into data stores. Triggers — Anomalous behavior is detected in real-time and further downstream actions are triggered accordingly. For example, unusual behavior of sensor devices generating actions. Data enrichment — Live data is enriched with more information by joining it with a static dataset allowing for a more complete real-time analysis. Complex sessions and continuous learning — Events related to a live session (e.g. user activity after logging into a website or application) are grouped together and analyzed. In some cases,

10

Jul

General availability of user behavior analytics tools in Azure Application Insights

At Microsoft Build 2017, we introduced a set of user behavior analytics tools for Application Insights as a preview. Since then, we’ve listened to your feedback, adding additional capabilities and squashing bugs. We’ve also used these user behavior analytics tools on themselves, finding opportunities to improve your experience without you even having to ask!

With this additional polish, today we’re graduating these tools out of preview to general availability. You can expect these tools – Users, Sessions, Events, User Flows, Funnels, Retention, Cohorts, and Impact – to be stable, well-supported parts of Application Insights going forward. 

How can I try these tools?

Users, Sessions, Events, and the other user behavior analytics tools are part of each Application Insights resource in the Azure portal. To get started with Application Insights, follow one of the quickstarts based on your app’s stack. Once you have an Application Insights resource, you’ll find the user behavior analytics tools in the left menu under “Usage.”

What’s new since last year?

A lot! Users, Sessions, and Events were re-built from the ground up to be more responsive, load more quickly, and provide more insights automatically. Learn more about Users, Sessions, and Events.

We also added six

09

Jul

Power BI Embedded dashboards with Azure Stream Analytics

Azure Stream Analytics is a fully managed “serverless” PaaS service in Azure built for running real-time analytics on fast moving streams of data. Today, a significant portion of Stream Analytics customers use Power BI for real-time dynamic dashboarding. Support for Power BI Embedded has been a repeated ask from many of our customers, and today we are excited to share that it is now generally available.

What is Power BI Embedded?

Power BI Embedded simplifies how ISVs and developers can quickly add stunning visuals, reports, and dashboards to their apps. By enabling easy-to-navigate data exploration in their apps, ISVs help their customers make quick, informed decisions in context. This also enables faster time to market and competitive differentiation for all parties.

Additionally, Power BI Embedded enables users to work within the familiar development environments, Visual Studio or Azure.

Using Azure Stream Analytics with Power BI Embedded

Using Power BI with Azure Stream Analytics allows users of Power BI Embedded dashboards to easily visualize insights from streaming data within the context of the apps they use every day. With Power BI Embedded, users can also embed real-time dashboards right in their organization’s web apps.

No changes are required for your existing

09

Jul

Power BI Embedded dashboards with Azure Stream Analytics

Azure Stream Analytics is a fully managed “serverless” PaaS service in Azure built for running real-time analytics on fast moving streams of data. Today, a significant portion of Stream Analytics customers use Power BI for real-time dynamic dashboarding. Support for Power BI Embedded has been a repeated ask from many of our customers, and today we are excited to share that it is now generally available.

What is Power BI Embedded?

Power BI Embedded simplifies how ISVs and developers can quickly add stunning visuals, reports, and dashboards to their apps. By enabling easy-to-navigate data exploration in their apps, ISVs help their customers make quick, informed decisions in context. This also enables faster time to market and competitive differentiation for all parties.

Additionally, Power BI Embedded enables users to work within the familiar development environments, Visual Studio or Azure.

Using Azure Stream Analytics with Power BI Embedded

Using Power BI with Azure Stream Analytics allows users of Power BI Embedded dashboards to easily visualize insights from streaming data within the context of the apps they use every day. With Power BI Embedded, users can also embed real-time dashboards right in their organization’s web apps.

No changes are required for your existing

09

Jul

Azure.Source – Volume 39
Azure.Source – Volume 39

Now in preview

Azure Event Hubs and Service Bus VNET Service Endpoints in public preview – Azure Event Hubs and Service Bus joins the growing list of Azure services enabled for Virtual Network Service Endpoints. Virtual Network (VNet) service endpoints extend your virtual network private address space and the identity of your VNet to the Azure services, over a direct connection. Endpoints allow you to secure your critical Azure service resources to only your virtual networks. Traffic from your VNet to the Azure service always remains on the Microsoft Azure backbone network.

IP filtering for Event Hubs and Service Bus – IP Filter rules are now available in public preview for Service Bus Premium and Event Hubs Standard and Dedicated price plans. For scenarios in which you want Service Bus or Azure Event Hubs to only be accessible from certain well-known sites, IP filter rules enable you to configure when to reject or accept traffic originating from specific IPv4 addresses.

New Azure #CosmosDB Explorer now in public preview – Azure Cosmos DB Explorer (https://cosmos.azure.com) is a full-screen, standalone web-based version of the Azure Cosmos DB Data Explorer found in the Azure portal, which provides a rich and unified developer experience

09

Jul

Azure.Source – Volume 39
Azure.Source – Volume 39

Now in preview

Azure Event Hubs and Service Bus VNET Service Endpoints in public preview – Azure Event Hubs and Service Bus joins the growing list of Azure services enabled for Virtual Network Service Endpoints. Virtual Network (VNet) service endpoints extend your virtual network private address space and the identity of your VNet to the Azure services, over a direct connection. Endpoints allow you to secure your critical Azure service resources to only your virtual networks. Traffic from your VNet to the Azure service always remains on the Microsoft Azure backbone network.

IP filtering for Event Hubs and Service Bus – IP Filter rules are now available in public preview for Service Bus Premium and Event Hubs Standard and Dedicated price plans. For scenarios in which you want Service Bus or Azure Event Hubs to only be accessible from certain well-known sites, IP filter rules enable you to configure when to reject or accept traffic originating from specific IPv4 addresses.

New Azure #CosmosDB Explorer now in public preview – Azure Cosmos DB Explorer (https://cosmos.azure.com) is a full-screen, standalone web-based version of the Azure Cosmos DB Data Explorer found in the Azure portal, which provides a rich and unified developer experience

09

Jul

Azure Marketplace new offers June 1–15
Azure Marketplace new offers June 1–15

We continue to expand the Azure Marketplace ecosystem. From June 1 to 15, 21 new offers successfully met the onboarding criteria and went live. See details of the new offers below:

A10 Lightning ADC with Harmony Controller – SaaS: Gain cloud-native load balancing, advanced traffic management, central policy management, application security, per-application traffic visibility, analytics, and insights.

Actian Vector Analytic Database Enterprise Edition: Actian Vector is a developer-friendly high-performance analytics engine that requires minimal setup, provides automatic tuning to reduce database administration effort, and enables highly responsive end-user BI reporting.

ADFS 4.0 Server Windows 2016: Quickly deploy a new ADFS 2016 server preloaded with the ADFS role, ADFS PowerShell module, and prerequisites. Add the VM to your Active Directory domain and follow the setup GUI to get Active Directory Federation Services up and running.

Build Agent for VSTS: This solution template simplifies the deployment of a private build agent to a single click. You can create a full deployment of private build agents for VSTS on Azure virtual machines using your Azure subscription.

CIS SUSE Linux