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Become your organization’s strategic advisor by using Machine Learning and Power BI

In this series of blog posts, I will provide a step by step guide on how to become the change agent that puts your organization on a path towards continuous improvement using the most valuable decision support techniques. I prefer the term decision support over business intelligence since it emphasizes the path to action.


Each post has a how-to section which assumes basic knowledge of Power BI and working knowledge of analytics and business reporting. If you are new to Power BI I recommend starting with the Guided Learning and then returning to this series. While most analysis in this blog is done with the programming language R I have tried to keep the scripts so generic that you will be able to apply them to your own data even without any prior experience of programming. To open the example files on your computer you will need Power BI Desktop and R installed.


In addition to explaining how you apply these techniques to your own data I will share examples of how I have found businesses successfully using them to drive deeper insights and better business outcomes. Most of these techniques however are general enough to be valuable for a broad range of scenarios so if you have ideas or experience of additional use cases, please share them in the comments section below.


Part One: Strategic decisions support through business driver analysis

Part Two: Facilitating business performance reviews

Part Three: Revenue and forecasting

Part Four: Managing complexity

Part Five: Quantifying business impact of previous investments

Part Six: Visualizing and interacting with your Azure Machine Learning Studio experiments