Your data is going places

There are still a lot of people who do not believe BI and cloud go together. "My data is too valuable to store anywhere else but on premise!". Most of the times we are talking about gut feeling here. It is not a strange thought either. But the funny thing is: maybe your data is
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Run Azure Stream Analytics job from UWP app

  Working with the newest technologies is great and frustrating. I can create solutions I’ve never made before while complaining about the outdated/incomplete documentation. I had one of those feelings while working with Azure Stream Analytics (ASA). My solution worked but there was one ‘elementary and simple’ thing I wanted: Start the ASA-jobs within my
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Automated Testing for the Data Warehouse

Case: we've integrated two sources of customers. We want to add a third source. Q: How do we at the same time know that our current integration and solutions will continue to work while at the same time integrating the new sources? A: Test it. Q: How do we get faster deployments and more stability? A: Automate the tests, so
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Azure ML Thursday 6: xgboost in R

Last Azure ML Thursdays we explored how to do our Machine Learning in Python. Python in Azure ML doesn't include one particularly succesful algorithm though - xgboost. Python packages are available, but just not yet for Windows - which means also not inside Azure ML Studio. But they are available inside R! Today, we take the same approach
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