Cleaning Dirty Data With Power Query In Power Bi
 

| Duration: 0h 46m
Master Data Cleaning with Power Query with 6 very dirty data case-studies in 45 Minutes
What you'll learn
Through 6 different very dirty datasets, you will master Data Cleaning with Power Query
You will understand the analytical thinking that makes you become excellent at data cleaning
You will learn different Power Query techniques for cleaning dirty data
You will also learn how to leverage and combine Power Query user interface buttons to complete data cleaning tasks
Requirements
No programming experience required
A Windows computer with minimum of Windows 10 OS
Power BI Desktop Installation
You should have an open mind to learning
Basic knowledge of Power BI and Power Query
Description
Cleaning Dirty Data with Power Query in Power BI is a must-know skill for any Power BI Analyst. It is known that Data Analysts and Data Scientists spend 60 to 80% of their time cleaning and preparing data. Although, most people are not conscious of the reason why this is the case. Simply put, the success of the entire flow of data from it's raw for to insights depend on how good the data is.In this Cleaning Dirty Data with Power Query in Power BI Course, 5x Microsoft MVP and Microsoft Certified Trainer, Ahmed Oyelowo will teach you the psychology and the technical aspects of cleaning dirty data, using Power Query in Microsoft Power BI.Why should you take this course?Explanations to complex dirty data are simplifiedYou will not only learn the steps and the How, you will understand the WhyThere are 6 different dirty data of the dirtiest data you can find anywhere that is treated in the course. This will let you understand the approach of thinking to solve dirty data problemsAll the dirty data cleaning insights is packed in about 45 minutes of instructionsYou will have the dirty data files, so you can use to practice and include in your project portfolios
Power BI Beginners,Anyone preparing for Power BI Certification,Data Analysts and Data Scientists,Aspiring Data Analysts and Data Scientists,Working Professionals,Excel users,Tableau users,Qlik users,R and Python programmers,SQL and Database Professionals,Intermediate Power BI users