About Paul Bunting

Experienced Software Architect with a demonstrated 20+ years’ developing solutions for the manufacturing and architectural design industries. Skilled in the design and creation of advanced analytical systems for real time system monitoring and process improvements. A focussed professional with keen attention to detail and adaptive approach to development and solution design. Specialist in • Enterprise Manufacturing Intelligence • Real Time Processing and Analytics • Big Data Analytics • Machine Learning and Data Science • IoT Analytics

AI for security: Microsoft Security Risk Detection makes debut

Full details at: – https://blogs.microsoft.com/next/2017/07/21/ai-for-security-microsoft-security-risk-detection-makes-debut/

Microsoft is making a cloud service that uses artificial intelligence to track down bugs in software generally available, and it will begin offering a preview version of the tool for Linux users as well.

Microsoft Security Risk Detection, previously known as Project Springfield, is a cloud-based tool that developers can use to look for bugs and other security vulnerabilities in the software they are preparing to release or use. The tool is designed to catch the vulnerabilities before the software goes out the door, saving companies the heartache of having to patch a bug, deal with crashes or respond to an attack after it has been released.

New M Functionality And Behaviour In Power BI Custom Data Connectors

Chris Webb's BI Blog

Over the past few weeks I’ve spent some time playing around with Power BI custom data connectors and while I don’t have anything to share publicly yet (other people are way ahead of me in this respect – see the work of Igor Cotruta, Miguel Escobar and Kasper de Jonge among others) I have learned some interesting things that are worth blogging about.

First of all, the data privacy rules around combining data from different data sources do not apply in custom data connector code. As the docs say here:

Data combination checks do not occur when accessing multiple data sources from within an extension. Since all data source calls made from within the extension inherit the same authorization context, it is assumed they are “safe” to combine. Your extension will always be treated as a single data source when it comes to data combination rules. Users would…

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Azure SQL Data Warehouse: Troubleshoot with the Resource Health check

Azure DW Resource HealthAzure DW Resource Health2 New update for Azure SQL Data Warehouse…

Reduce troubleshooting time with the upgraded Resource Health check for SQL Data Warehouse.

This upgrade considers the health status of all components of the SQL Data Warehouse architecture, which includes each SQL database distribution and the SQL Data Warehouse engine on each compute node. Login and heartbeat signals of each component are emitted at least once every 2 minutes, providing you a low-latency, holistic view of the health status of your data warehouse. If your instance is Unavailable, we will provide the reason along with recommended actions that you should perform.

The Resource Health check can detect unavailability reasons, such as when your instance is pausing, scaling, or upgrading. This feature also detects when there are any connection issues, whether they are user connections or inner SQL database connections.

You check the health of SQL Data Warehouse by signing in to the Azure portal and clicking the Resource Health blade.

Source: – https://azure.microsoft.com/en-us/updates/azure-sql-data-warehouse-troubleshoot-with-the-resource-health-check/

Free course on Deep Learning for Self-Driving Cars

self drive cars.pngA free course and introduction to deep learning through the applied task of building a self-driving car. Taught by Lex Fridman.

Visit http://selfdrivingcars.mit.edu/ for full details of “MIT 6.S094: Deep Learning for Self-Driving Cars“.

RESTful interactions with Azure Cosmos DB resources using the DocumentDB API, CRUD operations, API for MongoDB and additional quick starts

Azure Cosmos DB is a globally distributed system that supports the document, graph, and key-value data models which Microsoft have classified as a multi-model database service for mission-critical systems.

It also supports both the API for MongoDB and the DocumentDB API for creating, querying, and managing resources.

If you would like to understand how to answer any of the following questions: –

  • How do the standard HTTP methods work with Azure Cosmos DB resources?
  • How do I create a new resource using POST?
  • How do I register a stored procedure using POST?
  • How does Azure Cosmos DB support concurrency control?
  • What are the connectivity options for HTTPS and TCP?
Cosmos DB - interactions-with-resources2

Interaction model using the standard HTTP methods

Then take a look at Azure Cosmos DB REST API for full details first published on 18th July 2017 which covers these topics.


If interested in performing CRUD operations using REST, see Common tasks using the Azure Cosmos DB REST API.


If interested in performing CRUD operations using C# and REST, see the REST from .NET Sample on GitHub which can help you out.


If interested in more details of the MongoDB API, then see Introduction to Azure Cosmos DB: API for MongoDB which covers the benefits of using Azure Cosmos DB for MongoDB applications.

cosmosdb-mongodb

MongoDB wire protocol


… and finally if looking for help getting started then the following MongoDB quick starts will help you out: –

and also: –