In this video, learn about the heat map and image layer visualizations in side of Azure Maps. Heat maps are used to represent the density of data using a range of colors. They are often used to show the data “hot spots” on a map and are great to help understand data. The heat map layer also supports weighted data points to help bring the most relevant information to the surface.

The image layer allows you to overlay georeferenced images on top of the map so that they move and scale as you pan and zoom the map. This is great for building floor plans, overlaying old maps, or imagery from a drone.

Related Links:

In this episode of Five Things, John Papa and Jeff Hollan bring you five reasons you should check out Azure Functions today. You can also listen to Jeff dive deeper into serverless on his recent episode of Real Talk JavaScript.

Data integration is complex with many moving parts. It helps organizations to combine data and complex business processes in hybrid data environments. Failures are very common in data integration workflows. This can happen due to data not arriving on time, functional code issues in your pipelines, infrastructure issues, etc.

A common requirement is the ability to rerun failed activities within data integration workflows. In addition, sometimes you need to rerun activities to re-process data due to an error upstream in data processing. Azure Data Factory now enables you to rerun the entire pipeline or choose to rerun downstream from a particular activity inside a pipeline.

One of the promise of IoT is to allow bringing the intelligence of the Cloud to the Edge to run IoT data analytics as close as possible to the data source. This allows to reduce latencies, optimize performance and response times, support offline scenario, comply with privacy policies and regulations, reduce data transfer cost, and more…

One thing you really have to consider when bringing Artificial Intelligence to the edge is the hardware you will need to run these powerful algorithms. Ted Way from the Azure Machine Learning team joins Olivier on the IoT Show to discuss hardware acceleration at the Edge for AI. We will discuss scenarios and technologies Microsoft develops and uses to accelerate AI in the Cloud and at the Edge such as Graphic cards, FPGA, CPU,… To illustrate all this, Ted walks us through real life scenarios and demos IoT Edge running Machine Learning vision algorithms.

Learn more about hardware acceleration for AI at the Edge: https://docs.microsoft.com/azure/machine-learning/service/concept-accelerate-with-fpgas

Create a Free Account (Azure): https://aka.ms/aft-iot

Kirill Gavrylyuk joins Scott Hanselman to discuss new improvements for Azure Cosmos DB SDKs, including the new, idiomatic .NET SDK with friendlier, more intuitive programming model, better testability, better performance, .NET Standard 2.0 support, and now open sourced.     

 

Never miss an episode:

In this episode of the IoT Show, the subject is Azure Maps. Chris Pendleton, PM Lead for the service, gives us an overview of what Azure Maps is, who uses Azure Maps, how Azure Maps is being used across our customer base and how you can start using Azure Maps today.

Tune in to watch the Azure Maps IoT Show Deep Dive episode live on March 6 at 9AM PST or later on demand at https://aka.ms/iotshow/iotdeepdive/002

Learn more about Azure Maps: http://azuremaps.com

Create a Free Account (Azure): https://aka.ms/aft-iot

Modern data warehouses has the need to both handled relational data as well as non-structured information. In this session from Ignite, learn how modern data architectures combining technologies such as HDInsight, Data bricks and Azure Data Lake together with Azure SQL Data Warehouse has been used to deliver the modern data warehouse to large organizations.