Quick Tips: Renaming All Tables’ Columns in One Go in Power Query

Renaming All Tables' Columns in One Go in Power Query

I previously wrote a blog post explaining how to rename all columns in a table in one go with Power Query. One of my visitors raised a question in the comments about the possibility to rename all columns from all tables in one go. Interestingly enough, one of my customers had a similar requirement. So I thought it is good to write a Quick Tip explaining how to meet the requirement.

The Problem

You are connecting to the data sources from Power BI Desktop (or Excel or Data Flows). The columns of the source tables are not user friendly, so you require to rename all columns. You already know how to rename all columns of a table in one go but you’d like to apply the renaming columns patterns to all tables.

The Solution

The solution is quite simple. We require to connect to the source, but we do not navigate to any tables straight away. In my case, my source table is an on-premises SQL Server. So I connect to the SQL Server instance using the Sql.Database(Server, DB) function in Power Query where the Server and the DB are query parameters. Read more about query parameters here. The results would like the following image:

The Results of Sql.Database() Function in Power Query
The results of running the Sql.Database(Server, DB) function

As you see in the above image, the results include Tables, Views and Functions. We are not interested in Functions therefore we just filter them out. The following image shows the results after applying the filter:

Filtering out SQL Server Functions After Connecting from Power Query
Filtering out SQL Server Functions

If we look closer to the Data column, we see that the column is indeed a Structured Column. The structured values of the Data column are Table values. If we click on a cell (not on the Table value of the cell), we can see the actual underlying data, as shown in the following image:

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Finding Minimum Date and Maximum Date Across All Tables in Power Query in Power BI and Excel

Finding Minimum Date and Maximum Date Across All Tables in Power Query in Power BI and Excel

When we talk about data analysis in Power BI, creating a Date table is inevitable. There are different methods to create a Date table either in DAX or in Power Query. In DAX you my use either CALENDAR() function or CALENDARAUTO() function to create the Date table. In Power Query you may use a combination of List.Dates()#date() and #duration() functions. Either way, there is one point that is always challenging and it is how to find out a proper date range, starting from a date in the past and ending with a date in the future, that covers all relevant dates within the data model. One simple answer is, we can ask the business. The SMEs know what the valid date range is..

While this is a correct argument it is not always the case. Especially with the Start Date which is a date in the past. In many cases the business says:

Lets’s have a look at the data to find out.

That is also a correct point, we can always a look at the data, find all columns with either Date or DateTime datatypes then sort the data in ascending or descending order to get the results. But what if there many of them? Then this process can be very time consuming.

Many of you may already thought that we can use CALENDARAUTO() in DAX and we are good to go. Well, that’s not quite right. In many cases there are some Date or DateTime columns that must not be considered in our Date dimension. Like Birth Date or Deceased Date. More on this later in this post.

In this post I share a piece of code I wrote for myself. I was in a situation to identify the Start Date and the End Date of the date dimension many times, so I thought it might help you as well.

How it works?

The Power Query expressions I share in this post starts with getting all existing queries using:

  • #sections intrinsic variable
  • Filtering out the current query name, which is GetMinMaxAllDates in my sample, to avoid getting the following error:

Expression.Error: A cyclic reference was encountered during evaluation.

Expression.Error: A cyclic reference was encountered during evaluation.
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Quick Tips, Power BI Desktop, Query Parameters, Part 4, Passing Power Query Parameter Values to SQL Server Stored Procedures

I have written 3 blogposts about query parameters in the past.

This is the fourth one in the form of Quick Tips. Here is the scenario. One of my customers had a requirement to get data from a Stored Procedure from SQL Server. She required to pass the values from a Query Parameter back to SQL Server and get the results in Power BI.

The solution is somewhat easy. I created a simple stored procedure in AdventureWorksDW2019 as below:

CREATE PROCEDURE SP_Sales_by_Date 
	@date int
AS
BEGIN
	SET NOCOUNT ON;
	SELECT *
	FROM [dbo].[FactInternetSales]
	WHERE OrderDateKey >= @date
END
GO

In Power BI Desktop, get data from SQL Server, then:

  • Enter Server name
  • Enter Database name
  • Select Data Connectivity Mode
  • Expand the Advanced options
  • Type in a SQL statement to call the stored procedure like below:
exec SP_Sales_by_Date @date = 20140101
  • Click OK
Get Data From SQL Server using SQL Statements in Power BI Desktop
  • Click Transform Data
Transform Data in Power BI Desktop

Now we need to create a Query Parameter. In my sample I create a DateKey in Decimal Number data type:

Creating New Query Parameter in Power BI Desktop
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Quick Tips: Time Dimension with Time Bands at Seconds Granularity in Power BI and SSAS Tabular

Time Dimension with Time Bands at Seconds Granularity in Power BI and SSAS Tabular

I wrote some other posts on this topic in the past, you can find them here and here. In the first post I explain how to create “Time” dimension with time bands at minutes granularity. Then one of my customers required the “Time” dimension at seconds granularity which encouraged me to write the second blogpost. In the second blogpost though I didn’t do time bands, so here I am, writing the third post which is a variation of the second post supporting time bands of 5 min, 15 min, 30 min, 45 min and 60 min while the grain of the “Time” dimension is down to second. in this quick post I jump directly to the point and show you how to generate the “Time” dimension in three different ways, using T-SQL in SQL Server, using Power Query (M) and DAX. Here it is then:

Time Dimension at Second Grain with Power Query (M) Supporting Time Bands:

Copy/paste the code below in Query Editor’s Advanced Editor to generate Time dimension in Power Query:

let
Source = Table.FromList({1..86400}, Splitter.SplitByNothing()),
    #"Renamed Columns" = Table.RenameColumns(Source,{{"Column1", "ID"}}),
    #"Time Column Added" = Table.AddColumn(#"Renamed Columns", "Time", each Time.From(#datetime(1970,1,1,0,0,0) + #duration(0,0,0,[ID]))),
    #"Hour Added" = Table.AddColumn(#"Time Column Added", "Hour", each Time.Hour([Time])),
    #"Minute Added" = Table.AddColumn(#"Hour Added", "Minute", each Time.Minute([Time])),
    #"5 Min Band Added" = Table.AddColumn(#"Minute Added", "5 Min Band", each Time.From(#datetime(1970,1,1,0,0,0) + #duration(0, 0, Number.RoundDown(Time.Minute([Time])/5) * 5, 0))  +  #duration(0, 0, 5, 0)),
    #"15 Min Band Added" = Table.AddColumn(#"5 Min Band Added", "15 Min Band", each Time.From(#datetime(1970,1,1,0,0,0) + #duration(0, 0, Number.RoundDown(Time.Minute([Time])/15) * 15, 0))  +  #duration(0, 0, 15, 0)),
    #"30 Min Band Added" = Table.AddColumn(#"15 Min Band Added", "30 Min Band", each Time.From(#datetime(1970,1,1,0,0,0) + #duration(0, 0, Number.RoundDown(Time.Minute([Time])/30) * 30, 0))  +  #duration(0, 0, 30, 0)),
    #"45 Min Band Added" = Table.AddColumn(#"30 Min Band Added", "45 Min Band", each Time.From(#datetime(1970,1,1,0,0,0) + #duration(0, 0, Number.RoundDown(Time.Minute([Time])/45) * 45, 0))  +  #duration(0, 0, 45, 0)),
    #"60 Min Band Added" = Table.AddColumn(#"45 Min Band Added", "60 Min Band", each Time.From(#datetime(1970,1,1,0,0,0) + #duration(0, 0, Number.RoundDown(Time.Minute([Time])/60) * 60, 0))  +  #duration(0, 0, 60, 0)),
    #"Removed Other Columns" = Table.SelectColumns(#"60 Min Band Added",{"Time", "Hour", "Minute", "5 Min Band", "15 Min Band", "30 Min Band", "45 Min Band", "60 Min Band"}),
    #"Changed Type" = Table.TransformColumnTypes(#"Removed Other Columns",{{"Time", type time}, {"Hour", Int64.Type}, {"Minute", Int64.Type}, {"5 Min Band", type time}, {"15 Min Band", type time}, {"30 Min Band", type time}, {"45 Min Band", type time}, {"60 Min Band", type time}})
in
#"Changed Type"
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