Explore the differences between loading data in Azure Machine Learning Lab and PowerBI in this informative conference talk from PASS Data Community Summit. Learn about decision support systems, data visualization, and prediction models through a practical case study. Discover key steps in creating experiments and reports, data cleansing techniques, and effective data manipulations. Gain insights into asking the right questions for your model and understanding statistics in prediction models. Examine how to predict average late departures and identify suitable data visualization cases for PowerBI. Enhance your skills in predictive analytics and data-driven decision-making with Azure Machine Learning Studio and PowerBI.
Azure Machine Learning Studio and PowerBI - Predictive Analytics
PASS Data Community Summit via YouTube
Overview
Syllabus
Intro
Yana Berkovich
Azure Machine Learning Lab & PowerB
Who? What? Why?
Getting the Data - Decision Support System and the tip of the iceberg
Case Study
Visualizing the Data PowerBI
Data Cleansing
Data Manipulations
Main Steps in creating an Experiment / Report
Which Questions do we ask our Model?
What is a prediction model?
Statistics and prediction models How do we predict the average late departure?
Which of the following is a good fit for a data visualization case in powerBI?
Taught by
PASS Data Community Summit
