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This post explains how to update Azure Analysis Services model schemas from inside custom .NET applications. Whilst not a common scenario for most, it shows that this is easy to do using the AMO SDK. So, there’s nothing stopping you from developing complex and rich end-user functionality over the top of your data analysis solutions – providing run-time, user-driven schema changes like “what if” analysis.


Wardley Maps are a fantastic tool to help provide situational awareness, in order to help you make better decisions. We use Wardley Maps to help our customers think about the various benefits and trade-offs that can be made when migrating to the Cloud. In this blog post, Jess Panni demonstrates how we used Wardley Maps to plan the migration of OceanMind to Microsoft Azure, and how the maps highlighted where the core value of their platform was, and how PaaS and Serverless services offered the most value for money for the organisation.


Optimising C# for a serverless environment

by Carmel Eve

In our recent project with OceanMind we used #AzureFunctions to process marine vessel telemetry from around the world. This involved processing huge quantities of data in close to real time. We optimised our processing for a #serverless environment, the outcome of which being that the compute would cost less than £10 / month!

This post summarises some of the techniques we used, including some concrete examples of optimisations we made.

#bigdata #dataprocessing #dataanalysis #bigcompute


Integrating Azure Analysis Services into custom applications doesn’t just mean read-only data querying. But if your application changes the underlying model, it will need to be re-processed before the changes take effect. This post describes how to use the REST API for Azure Analysis Services inside a custom .NET application to perform asynchronous model refreshes, meaning your applications can reliably and efficiently deal with model updates.


As part of our work with OceanMind, endjin wrote a high performance .NET AIS parser. AIS (Automatic Identification System) is how commercial ships report location information. This blog describes the parser, and the performance techniques it uses.


Being able to construct DAX queries dynamically in C# means the possibilities are endless in terms of integrating Azure Analysis Services queries into your custom applications, and with the code samples in this post, you have everything you need to get started.


The theme of this year’s British Science Week (6 – 15 March 2020) is “Our Diverse Planet”. We’ll be getting involved by speaking to school children about the work we’ve been doing with Oxfordshire-based OceanMind (part of the Microsoft AI for Good programme) to help them combat illegal fishing, hopefully inspiring some of the next generation of data scientists!


The Azure CNAB Quickstart Templates we’ve created are only half the story. Much of the work we’ve done over the last few months involved the authoring, contribution and DevOps pipelines required to support an open source project. The project is inspired by the original Azure Quickstart Templates – which over the last 5 years has grown to over 850 templates. In this post we’re going to explain how you can author CNAB templates and contribute them.


Setting up Porter on Windows

by Mike Larah

Porter is a tool based on the CNAB (Cloud Native Application Bundle) spec. It can be used for building, managing, and installing application bundles. This guide will walk you through how to get set up with Porter on Windows.


In partnership with Microsoft, we have released Azure CNAB Quickstarts Library on GitHub. CNAB (Cloud-Native Application Bundle) is a new specification designed for facilitating the packaging, installation, upgrading and uninstallation of cloud-native solutions in the cloud, on-premise or on the edge. We’ve created a number of quickstarts covering Apache Airflow, Azure Kubernetes Service, Ghost, Kubeflow, SQL Server Always On and Wordpress to help demonstrate the power of CNAB and Porter.


In this post we show how a combination of Kubernetes, Azure Durable Functions and Azure API Management can be used to make legacy batch processing code available as a RESTful API. This is a great example of how serverless technologies can be used to expose legacy software to the public internet in a controlled way, allowing you to reap some of the benefits of a cloud first approach without fully rewriting and migrating existing software.


Integrating Azure Analysis Services into custom applications means more than just querying the data. By surfacing the metadata in your models, you can build dynamic and customisable UIs and APIs, tailored to the needs of the client application. This post explains how easy it is to query model metadata from .NET, so you can create deeper integrations between your data insights and your custom applications.


One of the first steps in integrating Azure Analysis Services into your applications is creating and opening a connection to the server – just like any other database technology. This post explains the ins and outs of creating Azure Analysis Services connections, including code samples for each of the key scenarios. 


NDC London 2020 – My highlights

by Ed Freeman

Ed attended NDC London 2020, along with many of his endjin colleagues. In this post he summarises and reflects upon his favourite sessions of the conference including; “OWASP Top Ten proactive controls” by Jim Manico, “There’s an Impostor in this room!” by Angharad Edwards, “How to code music?” by Laura Silvanavičiūtė, “ML and the IoT: Living on the Edge” by Brandon Satrom, “Common API Security Pitfalls” by Philippe De Ryck, and “Combatting illegal fishing with Machine Learning and Azure – for less than £10 / month” by Jess Panni & Carmel Eve.


Along with several of my endjin colleagues, I attended NDC London in January this year – here’s a run through of the sessions I attended on Day 3 and my thoughts. This final day was a mixed bag, taking in talks on drumming and AKKA.net, as well as something a bit more close to home – a session from endjin’s own Jess Panni and Carmel Eve on our recent project for OceanMind.


Along with several of my endjin colleagues, I attended NDC London in January this year – here’s a run through of the sessions I attended on Day 2 and my thoughts. This day was UI heavy, with sessions on Vuejs and UI testing, but I also learned more about GraphQL and writing high performance C# code.


A retrospective of my first day at NDC London 2020, taking in sessions on AI and Machine Learning, Capability Mapping, Micro Frontends, Diagnostics and Blazor.


With a variety of integration support through client SDKs, PowerShell cmdlets and REST APIs, it can be hard to know where to start with integrating Azure Analysis Services into your custom applications. This posts walks through the options, and lays out a simple guide to choosing the right framework.


We’ve done a lot of work at endjin with Azure Analysis Services over the last couple of years – but none of it has been what you’d call “traditional BI”. We’ve pulled, twisted and bent it in all sorts of directions, using it’s raw analytical processing power to underpin bespoke analysis products and processes. This post explains some of the common (and not-so-common) reasons why you might want to do similar things, and how Azure Analysis Services might be the key to unlocking your data insights.


AI for Good Hackathon

by Ian Griffiths

Towards the end of last year, Microsoft invited endjin along to a hackathon session they hosted at the IET in London as part of their AI for Good initiative. I’ve been thinking about the event and the broader work Microsoft is doing here a lot lately, because it gets to the heart of what I love about working in this industry: computers can magnify our power to do to good.


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