Identify Patterns and Trends in Power BI
Offered By: Pluralsight
Course Description
Overview
This course will teach you about the Power BI visual analysis features so that you have the knowledge and know how to apply this and answer related questions in the PL-300 exam.
To be an effective data analyst, you need to know what types of patterns can be displayed, what each pattern reveals, and which tool to use to plot a particular pattern. In this course, Identify Patterns and Trends in Power BI, you will learn the visual analysis features needed for the PL-300 exam. First, you will explore the different types of charts and when you should use them. Then, you will dive into how to use a series of tools and techniques to identify different types of patterns in the data. Finally, you will discover how to use a new generation of charts and tools that use artificial intelligence and machine learning to speed up the process of analyzing data. At the end of the course, you will have the information you need to answer questions on this topic in the PL-300 exam.
To be an effective data analyst, you need to know what types of patterns can be displayed, what each pattern reveals, and which tool to use to plot a particular pattern. In this course, Identify Patterns and Trends in Power BI, you will learn the visual analysis features needed for the PL-300 exam. First, you will explore the different types of charts and when you should use them. Then, you will dive into how to use a series of tools and techniques to identify different types of patterns in the data. Finally, you will discover how to use a new generation of charts and tools that use artificial intelligence and machine learning to speed up the process of analyzing data. At the end of the course, you will have the information you need to answer questions on this topic in the PL-300 exam.
Syllabus
- Course Overview 2mins
- Understanding Visual Analysis 59mins
- Analyzing Data with AI Visuals 45mins
Taught by
Andrew McSwiggan
Related Courses
Social Network AnalysisUniversity of Michigan via Coursera Intro to Algorithms
Udacity Data Analysis
Johns Hopkins University via Coursera Computing for Data Analysis
Johns Hopkins University via Coursera Health in Numbers: Quantitative Methods in Clinical & Public Health Research
Harvard University via edX