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DAX / Power BI – Data Analysis Techniques Part 1

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Description

DAX / Power BI – Data Analysis Techniques Part 1 Download Now

10 different DAX and Power BI data analysis techniques covered in part 1 of this course What you’ll learn:
Anomaly detection analysis
Time series and forecasting analysis
Key Influencers analysis
Q and A analysis
Decomposition Tree analysis
Grouping and binning analysis
Geospatial analysis
Smart Narratives Analysis
Quick Insights analysis
Currency conversion useful for other types of analysis

Requirements
Some basic knowledge of DAX and Power BI would be helpful

Description
If you are a DAX and Power BI developer, or studying for the DA-100 exam, you almost certainly love to work with data, data of any kind. In fact, you might consider yourself a “data geek”. For non-native English speaking students this phrase, as used here, means an expert or enthusiast obsessed with a hobby or intellectual pursuit. In this case, the pursuit of data.

In this 4+ hour course we cover at least 10 different data analysis techniques including AI related data analysis techniques including Anomaly Detection, Key Influencer Analysis, Q&A analysis and Decomposition Tree analysis. We also cover time series and forecasting analysis, Smart Narrative analysis, Geospatial analysis, Quick Insight analysis, grouping and binning analysis and currency conversion, which is often included in other types of sales analysis.

There will be a part 2 to this course where we will pick up where we left off and cover at least the following types of analysis:

Cluster analysis

Cohort analysis

Segmentation analysis

R and Python integration analysis

Pareto Principal

Customer attrition analysis

Basket analysis

Variance analysis

Ranking 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.

Who this course is for
DAX and Power BI developers who love analyzing data!

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