Prep 2: Other Options for Key Influencers
The Key Influencers Power BI Desktop visual isn’t the only way to do more powerful analysis. Power BI offers several alternatives for performing powerful statistical analysis beyond the Key Influencers visual and these are presented
below:
Analyse in Excel: Power BI Desktop allows you to export data to Excel, where you can leverage its extensive statistical analysis capabilities. Excel provides various statistical functions, regression analysis, data modelling, and advanced
visualisation options that can help you uncover insights from your data.
DAX Calculations: Power BI’s Data Analysis Expressions (DAX) language enables you to create complex calculations and perform statistical calculations within measures and calculated columns. With DAX, you can implement functions such
as AVERAGEX, STDEV.P, VAR.S, and more, to calculate averages, standard deviations, variances, correlations, and other statistical measures.
R or Python Integration: Power BI Desktop allows integration with R and Python, two widely-used programming languages for statistical analysis. You can leverage the power of R or Python scripts to perform advanced statistical computations,
run machine learning algorithms, and generate visualisations that go beyond the built-in Power BI visuals.
Custom Visualisations: Power BI Desktop supports the integration of custom visualisations created by the community or developed in-house. You can explore custom visuals designed specifically for statistical analysis, such as box plots, scatter plots, histograms, or trend lines. These visuals can enhance your ability to analyse and interpret statistical patterns and relationships within your data.
Advanced Analytics with AI: If you want to crunch a lot of data, Power BI integrates with Azure Cloud to access Big Data and AI engines such Azure Fabric, Synapse, Cognitive Services and Azure Machine Learning, allowing you to incorporate
advanced analytics and machine learning models into your reports. In Fabric/Synapse can use pre-built AI model starter templates or develop your own models to perform tasks like sentiment analysis, anomaly detection, clustering,
forecasting, or regression analysis.
Statistical Modelling Tools: Power BI can connect to external statistical modelling tools like RStudio, Python IDEs (Integrated Development Environments) such as Jupyter Notebook or Anaconda, or other dedicated statistical analysis software.
You can import results from these tools into Power BI for visualisation and further analysis. These alternatives provide flexible options for performing powerful statistical analysis within Power BI Desktop outside of the Key Influencers visual. You can choose the method that best suits your specific requirements, skillset, volume of data and the complexity of the analysis you need to perform