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Keep shoppingDAX / Power BI - Data Analysis Techniques Part 2
242 students
DAX / Power BI - Data Analysis Techniques Part 2
10 additional DAX and Power BI data analysis techniques covered in this continuation course from part 1
Created byRandy Minder
Last updated 7/2021
English
What you'll learn
- Cohort Analysis
- Cross-selling Analysis
- Pareto Analysis
- Simple Clustering Analysis
- Ranking Analysis
- Attrition Analysis
- R Integration
- Percentile Analysis
- Scenario / Sensitivity Analysis
- Market Basket Analysis
Explore related topics
Course content
10 sections • 27 lectures • 4h 17m total length
Requirements
- Some basic knowledge of DAX and Power BI would be helpful
Description
DAX and Power BI offer a wide range of data analysis techniques. In fact, as you probably know, data analysis is at the heart of working with tools like Power BI and DAX. This is why we have created a two-course series of data analysis techniques using DAX and Power BI.
In Part 1 of this course we spend over four hours covering a wide range of very interesting topics such as anomaly detection, Key Influencer analysis, forecasting analysis, Decomposition Tree analysis, Q & A analysis and much more.
You can continue to improve your analysis skills with this 4+ hour course. We cover at least 10 more different and interesting data analysis techniques including:
Cohort Analysis
Cross-selling Analysis
Pareto Analysis
Simple Clustering Analysis
Ranking Analysis
Attrition Analysis
R Integration
Percentile Analysis
Scenario / Sensitivity Analysis
After we cover each technique, or at least most of them, you will have the opportunity to do a little practice to test, and further enforce what you have learned. This course would also be valuable for study towards the DA-100 exam.
A common question will be "is there going to be a part 3 to this series?" We have no plans for a part 3. If you would like other areas of analysis covered, let us know and we will add it to either part 1 or part 2.
Who this course is for:
- DAX and Power BI developers who love analyzing data!