Power Query M Language with Specialize in Web Scraping


Summary, Description

What is the vocabulary of formula M?

In every data analytics project, one of the most important and daunting activities is data transformation & data cleaning. To retrieve valuable insights, we need to plan the data to make it appropriate for study.

We have a Power question like an ETL for the data warehouse in the Power Bi environment. The power query generates M code, a formula language, whenever we perform some operation on the results. The vocabulary of the M formula includes a rich set of different data transformation & cleaning functions.

Why learn the vocabulary of the M formula?

Microsoft launches new versions of Power BI nearly every month, with new graphics features in the Power Bi ribbon. We do have to rely, however, on the specific characteristics of the graphical user interface of the power question.

By learning the language of Power Question M, we can solve this dependence. As the whole underlying auto-generated code would be in our hands, the M language is far more powerful than the Power demand.

In this course, you will learn all the Power Query M language building blocks to master it on your own.

This course will give you a simple guide to how to apply any available data transformation feature in the M language.

My name is Muhammad Asif, and I am going to be your tutor for this course. I have more than ten years of data & analytics experience with one of the leading companies in the world. I am a specialist in data analytics & management with a Microsoft approved solution.

For a separate line of services, I have built multiple data templates, dashboards & reports. You will benefit from my background, and I’m going to share every single thing. By simplifying hard concepts, I want to spread knowledge.

I wish you all the best for your trip in the language of the Strength BI & M recipe.
For whom this course is intended:

Users of Excel
Analysts of Results
Consultants on Corporate Intelligence
Engineers of Data
Scientists of Data


Course Link