This course establishes a framework for data analytics as a series of progressive steps starting with the data source and ending with the interpretation of results. We introduce fundamental concepts such as data analytics life cycle, data integrity, and the four types of data analytics (descriptive, diagnostic, predictive, and prescriptive). Students who complete this course will be equipped with the skills to identify the data analytics strategy used in a given situation and where they are in the data analytics life cycle.
Overview
Syllabus
- Introduction to Data Analysis
- In this lesson, we will introduce you to data analysis and what we will be covering in this course.
- Data Analytics Life Cycle
- In this lesson, we will learn how to solve data analysis issues using each step of the data analytics life cycle.
- Data Integrity
- In this lesson, we will review the importance of data integrity in data analysis, the components of data integrity, and how to identify and fix it.
- Types of Data Analytics & Statistics
- In this lesson, we will review each of the different types of data analytics and when to use them, along with statistics that pertain to each analytics type.
- Power BI Overview
- In this lesson, we will introduce Power BI and its capabilities as an analytics and data visualization tool.
- Out of the Box Analytics
- In this project, you will use what you learned about data analytics to analyze KPIs for a company and represent your analysis with effective visuals.
- Microsoft Power BI Workspace
- In this lesson, you'll learn how to set up a Windows desktop workspace to use Power BI
Taught by
Ivan Vega
