Business Intelligence with Microsoft Power BI - with Material - Column from Examples - Alphanumeric

The video tutorial explains how to handle alpha numerical data using Power Query. It covers extracting specific elements like first names, numbers, and text from mixed data. The tutorial demonstrates using the 'column from example' feature to simplify data extraction and highlights the importance of training the tool to recognize patterns. It also discusses the backend functions involved in the process and concludes with the benefits of using Power Query for data cleaning and visualization.

What feature is used to extract specific parts of alpha numerical data?

• Column from example

• Data filter

• Text splitter

• Number extractor

What is a key challenge when extracting the last number from mixed data?

• Finding the middle number

• Teaching the system to recognize patterns

• Identifying the first text

• Separating text from numbers

Which function is mentioned as being used in the backend for data extraction?

• Nested M functions

• VLOOKUP

• Data merge

• Text join

What is necessary to improve the accuracy of text extraction from alpha numerical data?

• Continuous training of the system

• Using more columns

• Increasing data size

• Reducing text length

What is one benefit of using Power Query for data handling?

• It is only for text data

• It helps in creating visuals and dashboards

• It requires no training

• It can only handle numerical data