Excel PowerQuery M code language – Part 3

ETL (Extract Transform Load) Data using M code - Our third part in an attempt to make you Ninja.

Created by: ajay parmar
Instructor -Excel,Vba ,Access, Access Vba,BI,PQ,G SHEETS

What Will I Learn?

• This is sequel of M code Powerquery and students are requested to first watch Part1 and Part2 also, if they are not expert in M code.
• Solving complex Projects using M code user defined function. One of your project is solved.
• You will learn how to work with Dates. Adding days, years,quarters will never be a challenge now.
• How to use M Functions which helps in extracting the text values using text functions. Know your left, right, mid and Find functions in M Code with practicals.
• How to reverse the strings How to remove the characters from a string.
• How to insert characters into a string.
• How to see if a string contains specific characters or not.
• Know your List functions like List dates. LIst union. List difference and do the complex lookups between two or more than two tables without getting into hassle
• You will see if you want to link other table headers into another tables , how to do the same. It is so amazing
• How to extract months, days, years from a date using date functions. One should know such things as we almost have date fields in every data.
• Know how to sum the cumulative numbers using list range function
• Student question solved - split year and status

Requirements

• You should have Excel 2010 or above version. Best is office 365 as it provides the intellisense.
• You must know M code basics and its Lists and records. If you do not know please refer to Part1 and Part2. Refer to document attached here for course links.
• This part3 is only for those students who have seen part1 and part2. It is a sequel to part2.

Target audience

• Business Analysts , Excel Users and MIS analysts who like to clean, transform the large or small datasets without complex excel formulas and without any vba.
• All those professionals and students who work with big data every day and find it challenging to shape up the most complex and unstructured data.