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We’re currently working on a project to migrate a customer from AWS to Azure. As always, we like to put a Continuous Delivery pipeline at the heart of the project to ensure there is zero friction pushing out changes across all dev, test and production environments. Two years ago I wrote about the process we […]


Automated R Deployments in Azure

by Jess Panni

It’s been great to see Microsoft embracing the R language on Azure, being able to easily operationalize R assets is changing the way organisations think about their analytical workloads. While it is trivial to publish an R model as a web service in Azure Machine Learning, there is still no easy way to integrate this […]


Machine Learning – the process is the science

by James Broome

As the interest in data science, predictive analytics and machine learning has grown in direct correlation to the amount of data that is now being captured by everyone from start ups to enterprise organisations, endjin are spending increasing amounts of time working with businesses who are looking for deeper and more valuable insights into their […]


We produced a booklet to coincide with our Future Decoded talk “The 100 Year Start-up: Embracing Disruption in Financial Services“, where we examine the challenges and opportunities in the Microsoft Cloud for the Financial Services Industry, covering the following topics: Security, Privacy & Data Sovereignty Data Ingestion, Transformation & Enrichment Big Compute Big Data – […]


As the interest in data science, predictive analytics and machine learning has grown in direct correlation to the amount of data that is now being captured by everyone from start ups to enterprise organisations, endjin are spending increasing amounts of time working with businesses who are looking for deeper and more valuable insights into their data. […]


Developing U-SQL: Local Data Folder

by Jess Panni

Those of you dabbling around with/in Azure Data Lake and Visual Studio will be aware that it is possible to run U-SQL scripts locally on your development machine. This is useful when developing and debugging scripts against small sets of data since you do not incur the overhead of submitting and running jobs up on Azure. U-SQL can access […]


A short while ago, I was trying to classify some data using Azure Machine Learning, but the training data was very imbalanced. In the attempt to build a useful model from this data, I came across the Synthetic Minority Oversampling Technique (SMOTE), an approach to dealing with imbalanced training data. This blog describes what I […]


Azure data services part 3: Azure Machine Learning

by Alice Waddicor

In parts 1 and 2 of this mini-series, I wrote brief intros to HDInsight and Stream Insight, Azure’s offerings for big data analytics and real-time analytics. Next up, Azure Machine Learning. What it’s for: Azure Machine learning provides a GUI with drag and drop pre-built components for carrying out predictive analytics. You can also plug […]


Azure data services part 2: Stream Insight

by Alice Waddicor

This blog is part of a series where I’m writing up my notes from a training session on Azure’s data services. The previous post dealt with Azure’s Hadoop implementation, HDInsight. This week, I’m going to write about Stream Insight. What it’s for: Stream Insight is an Azure service for real-time event processing. Use cases for […]


Azure data services part 1: HDInsight

by Alice Waddicor

Last Autumn, Richard Kerslake and I were lucky enough to land in the warmth of Barcelona, for a Microsoft Analytics training event. The sessions gave an introduction to Azure’s HDInsight, Stream Analytics and Machine Learning services. I’m going to write up a quick summary of what I learned about each service, starting with HDInsight. What […]