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Mastering Power Query, M Language with MS Excel
Direct Power Query Limitations- Error Handling
#1 Downloadable Case Study
Errors handling- While you Modify a Table / Delete a Table / Rename a Table (7:16)
Dynamically rename columns while avoid errors (6:42)
Perform a Case sensitive Advanced Filter (15:35)
Identify/Keep/Remove - Power Query error Rows in the Data Frames (5:10)
Null Handling values during query Results (addition / Multiplication / Division) (7:54)
Merge queries & case sensitive Duplicates - JOINS (5:56)
Solutions- Different Unpivot issues (9:16)
Power Query- Case Studies
#2 Downloadable Case Study
Date and Time – Convert for different time zone (5:20)
Understanding the Business Value of ‘Leave Data Part 1’ (7:14)
Understanding the Business Value of ‘Leave Data Part 2’ (7:14)
Stack the un-stack Data which is Uneven - Part 1 (5:10)
Stack the un-stack Data which is Uneven - Part 2 (4:49)
How to quickly combine multiple row data into single cell using this Reverse trick (7:55)
Power Query Ranking- Excel Magic Trick (6:35)
Date List – Allocating Fixed cost on monthly Basis (7:57)
Recording Prepaid Expenses each month (4:43)
Deep dive into Advanced Power query editor concepts and Power query- M Language
#3 Downloadable Case Study
Concept explained: M Language and Advanced query editor (9:11)
Power Query Parameters - Introduction (4:47)
Create / edit / deleting Parameters Using PQ interface (11:36)
Introduction - Microsoft Power Query Custom M Functions (4:13)
Microsoft Power Query Parameters and Power Query Interface -Custom M Functions (13:41)
Microsoft Power Query using advanced editor - Custom M function (11:14)
Nested calculation in Power Query- Power Query Conditional RANKIF based on custom M function (6:41)
Show Query Dependency and Grouped Queries (6:37)
Custom M Functions – Dynamic (ready to use) Patterns
#4 Downloadable Case Study
Introduction- Dynamic (ready to use) Custom M Function (2:36)
Vendor Ageing analysis with Approximate Match in Power Query (11:52)
Power Query Custom M- Code – Calculates working days between dates (6:01)
Identify/Keep/Remove - Power Query error Rows in the Data Frames
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