D.O.T.S. Power Query and M Intermediate
£485.00 – £13,500.00
This is the Dual Online Training Solution (D.O.T.S.) version of our Power Query and M Intermediate course. This course is designed for experienced Power BI users. Topics covered include: Working with Related Queries; Using Parameters; Parameters and Incremental Refresh; Assessing Data Quality; Reducing the Cardinality of Columns; Creating Non-Tabular Queries; and Dealing with Errors.
Description
This 1-day Power Query and M Intermediate course is designed for experienced Power BI users. It shows delegates how to control and customize the operations initially performed using the Power Query interface. Topics covered include: Data Loading and Query Dependencies; Using the Advanced Editor; Using Parameters; Parameters and Incremental Refresh; Assessing Data Quality; Reducing the Cardinality of Columns; Creating Non-Tabular Queries; and Dealing with Errors.
Our Dual Online Training Solution provides your staff with two modes of training: live instructor-led training is followed with three year’s access to the self-paced version of the same course. The material covered in the live training will be very similar to that covered in the self-paced video training. So, the self-paced training provides a very effective form of post-training reinforcement.
Course Outline
Data Loading and Query Dependencies
Duplicating and Referencing Queries
Disabling Data Loading
Using Query Dependencies view
Using the Advanced Editor
M Language Overview
Using the Formula Bar
Using the Advanced Editor
Understanding Variable Declaration
Editing M Code
Using Parameters
Parameters Overview
Parameterizing Data Source Information
Parameterizing Date Ranges
Applying Parameters as Filters
Using Merge Queries to Extend Parameter Filtering
Using Static Lists for Parameter Input
Using Dynamic Lists for Parameter Input
Using Parameters in a Template
Parameters and Incremental Refresh
What is Incremental Refresh
RangeStart and RangeEnd Parameters
Filtering the Main DateTime Column
Ensuring that Query Folding Will Occur
Configuring Incremental Refresh
Assessing Data Quality
Show Whitespace
Column Quality
Column Distribution
Column Profile
Column Profiling Based on Entire Dataset
Using the Table.Profile Function
Reducing the Cardinality of Columns
Overview of Column Cardinality
Optimizing Data Types
Isolating Data Types by Splitting
Reducing Cardinality by Grouping
Creating Non-Tabular Queries
Returning Earliest and Latest Dates
Replacing Errors with an Average Value
Additional information
Date | 4 Mar 2022(Tutor-led, Online), 10 May 2022(Tutor-led, Online), 12 Jul 2022(Tutor-led, Online), 27 Sep 2022(Tutor-led, Online), 22 Nov 2022(Tutor-led, Online), Private Training for up to 10 Users, Private Training for up to 20 Users, Private Training for up to 30 Users, Private Training for up to 40 Users, Private Training for up to 50 Users, Private Training for up to 60 Users, Private Training for up to 70 Users, Private Training for up to 80 Users, Private Training for up to 90 Users, Private Training for up to 100 Users |
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