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Overview

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Overview
Overview
Difficulty
Intermediate
Duration
1h 4m
Students
79
Ratings
5/5
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Description

Advanced Analysis with Power BI examines various methods for teasing out insights from data using statistical methodologies and presenting significant findings in visually compelling formats. The course starts with basic statistics such as standard deviation and then progresses to AI and machine learning analysis where Power BI does all the heavy lighting allowing the user to investigate and dynamically explore significant findings.

Learning Objectives

  • How to use Z-scores to display outliers and use the Outlier Detection visualization from Microsoft
  • How to use Power BI's Anomaly Detection and Fluctuation Analysis functionality
  • Use time-series forecasting to predict future data points with varying degrees of certainty
  • Use groups to classify categorical data and bins to categorize continuous data
  • Learn about Key Influencers
  • Use the Decomposition tree to drill down into a metric manually using known factors or let AI functionality determine which factors are the major contributors
  • Use the power of Azure's AI and machine learning to analyze text for positive and negative sentiment, keywords and phrases, and image tagging

Intended Audience

This course is intended for anyone who wants to discover insights hidden in their data.

Prerequisites

  • Have a basic understanding of statistics, like knowing the difference between a mean and median, a normal distribution, and conceptually how standard deviation is related to that
  • Know how to connect a data source, load data, and generally use the Power BI Desktop and Power Query Editor environments
  • AI Insights demonstration requires a PowerBi.com premium account
Transcript

This course is primarily hands-on demonstrations, where we start with outlier and anomaly detection functionality and how that relates to categorical and continuous data. This segues into forecasting with Time series analysis of continuous data. Then we look at how groups and bins are methods for classifying categorical and continuous data. We'll get into AI and machine learning-driven analysis and visualizations in the second half of the course. 

Key influencers and the decomposition tree chart lectures demonstrate the key features of powerful analysis and presentation tools. AI insights, the umbrella term for cognitive services available in Power BI, encompasses natural language processing, image tagging, and Azure machine learning integration. We'll use sentiment scoring and keyphrase extraction to analyze comments from a help desk database. There is a lot to cover, so let's crack on with outlier detection.

About the Author
Avatar
Hallam Webber
Software Architect
Students
19585
Courses
46
Learning Paths
7

Hallam is a software architect with over 20 years experience across a wide range of industries. He began his software career as a  Delphi/Interbase disciple but changed his allegiance to Microsoft with its deep and broad ecosystem. While Hallam has designed and crafted custom software utilizing web, mobile and desktop technologies, good quality reliable data is the key to a successful solution. The challenge of quickly turning data into useful information for digestion by humans and machines has led Hallam to specialize in database design and process automation. Showing customers how leverage new technology to change and improve their business processes is one of the key drivers keeping Hallam coming back to the keyboard.