Tag: DAX

Azure Analysis Services, BISM Tabular, Business Intelligence - BI, Data Warehousing - DW, DAX, Power BI, Power BI Desktop, Power BI Desktop RS, Power Pivot, Power Query, Quick Tips, Self-Service BI, SQL Server, SQL Server Analysis Services - SSAS, T-SQL

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])), Time.Type),
    #"Hour Added" = Table.AddColumn(#"Time Column Added", "Hour", each Time.Hour([Time]), Int64.Type),
    #"Minute Added" = Table.AddColumn(#"Hour Added", "Minute", each Time.Minute([Time]), Int64.Type),
    #"5 Min Band Added" = Table.AddColumn(#"Minute Added", "5 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/5) * 5) + 5, 0)), Time.Type),
    #"15 Min Band Added" = Table.AddColumn(#"5 Min Band Added", "15 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/15) * 15) + 15, 0)), Time.Type),
#"30 Min Band Added" = Table.AddColumn(#"15 Min Band Added", "30 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/30) * 30) + 30, 0)), Time.Type),
#"45 Min Band Added" = Table.AddColumn(#"30 Min Band Added", "45 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/45) * 45) + 45, 0)), Time.Type),
#"60 Min Band Added" = Table.AddColumn(#"45 Min Band Added", "60 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/60) * 60) + 60, 0)), Time.Type),
    #"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"})
in
    #"Removed Other Columns"
Continue reading “Quick Tips: Time Dimension with Time Bands at Seconds Granularity in Power BI and SSAS Tabular” →
Business Intelligence - BI, Data Visualisation, Power BI, Power BI Desktop, Power BI Service, Self-Service BI

Highlighting Below Avg Sales per Hierarchy Level with SWITCH() and ISINSCOPE() DAX Functions in Power BI

Highlighting Below Avg Sales per Hierarchy Level with SWITCH() and ISINSCOPE() DAX Functions in Power BI

I was working on a project a wee bit ago that the customer had conditional formatting requirement on a Column Chart.
They wanted to format the columns in the chart conditionally based on the average value based on the level of hierarchy you are at.
Here is the scenario, I have a Calendar hierarchy as below:

  • Calendar Hierarchy:
    • Year
    • Semester
    • Quarter
    • Month
    • Day

I use “Adventure Works DW2017, Internet Sales” Excel as my source in Power BI Desktop. If I want to visualise “Total Sales” over the above “Calendar Hierarchy” I get something like this:

Line Chart in Power BI, Total Sales by Year

Now I activate “Average Line” from “Analytics” tab of the Line chart.

Adding Average Line to Line Chart in Power BI

When I drill down in the line chart the Average line shows the average of that particular hierarchy level that I am in. This is quite cool that I get the average base on the level that I’m in code free.

Power BI, Drilling Donw in Line Chart

Easy, right?

Now, the requirement is to show the above behaviour in a “Column Chart” (yes! visualising time series with column chart, that’s what the customer wants) and highlight the columns with values below average amount in Orange and leave the rest in default theme colour.

So, I need to create Measures to conditionally format the column chart. I also need to add a bit of intelligent in the measures to:

  • Detect which hierarchy level I am in
  • Calculate the average of sales for that particular hierarchy level
  • Change the colour of the columns that are below the average amount

Let’s get it done!

Detecting Hierarchy Level with ISINSCOPE() DAX Function

Microsoft introduced ISINSCOPE() DAX function in the November 2018 release of Power BI Desktop. Soon after the announcement “Kasper de Jonge” wrote a concise blogpost about it.

So I try to keep it as simple as possible. Here is how is works, the ISINSCOPE() function returns “True” when a specified column is in a level of a hierarchy. As stated earlier, we have a “Calendar Hierarchy” including the following 5 levels:

  • Year
  • Semester
  • Quarter
  • Month
  • Day

So, to determine if we are in each of the above hierarchy levels we just need to create DAX measures like below:

ISINSCOPE Year		=	ISINSCOPE('Date'[Year])
ISINSCOPE Semester	=	ISINSCOPE('Date'[Semester])
ISINSCOPE Quarter	=	ISINSCOPE('Date'[Quarter])
ISINSCOPE Month		=	ISINSCOPE('Date'[Month])
ISINSCOPE Day		=	ISINSCOPE('Date'[Day])

Now let’s do an easy experiment.

  • Put a Matrix on the canvas
  • Put the “Calendar Hierarchy” to “Rows”
  • Put the above measures in “Values”
Detecting Year, Semester, Quarter, Month and Day hierarchy levels with ISINSCOPE in Power BI Desktop

As you see the “ISINSCOPE Year” shows “True” for the “Year” level. Let’s expand to the to the next level and see how the other measures work:

Continue reading “Highlighting Below Avg Sales per Hierarchy Level with SWITCH() and ISINSCOPE() DAX Functions in Power BI” →
Business Intelligence - BI, DAX, Power BI, Power BI Desktop, Power Query, Quick Tips, Self-Service BI

Quick Tips: How to Sort Matrix by Column in Descending Order

How to Sort Matrix by Column in Descending Order

Today Microsoft released Power BI Desktop March 2020 which I was hoping that it includes a simple feature on Matrix visual to be able to sort the Martix by column in descending order, but, it doesn’t. So, in this post I quickly show you how to sort Matrix by column in descending order.

Here is the scenario. One of my customers is building a report in Power BI showing sales by Year, Month and Day of Week in a Matrix as below.

Sorting Matrix Visual in Power BI
Sorting Matrix Visual in Power BI

Everything looks fine! But looking at the Matrix sorting quickly reveals that such feature is NOT available (YET). But the customer would like to see the Matrix sorted by Year in descending order, something like this.

Sorting Matrix by Column Headers in Descending Order
Sorting Matrix by Column Headers in Descending Order

Here is the solution which is super simple.

Continue reading “Quick Tips: How to Sort Matrix by Column in Descending Order” →
Business Intelligence - BI, DAX, Power BI, Power BI Desktop, Power BI Documenter, Power Query, Self-Service BI

Empower Your Story Telling Data Visualisation in Power BI with Colour Coding

Colour Coding in Power BI

This post has been waiting in my blogging list for a while and now this is my last post in 2019. I wish you all have a wonderful year ahead.

In this post I discuss a very important aspect of data visualisation; Colour Coding. I believe, colour coding is one the most powerful and efficient ways to provide proper information to the users. We learnt as human being that the colour can tell a lot about things. For instance, we look at green grass, if it is light green we immediately understand that the grass is quite fresh and healthy. When she gets a bit yellowish, we know that she’s perhaps thirsty. When it gets brown it is probably too late.

Another perfect example is traffic lights. When it is green, everyone is happy, when it is yellow, everyone is racing to pass the junction, well, I’m just kidding, some people tend to pass the yellow light while everyone knows they have to stop when traffic light is yellow right?? And… when it is red, we have to stop. Enough saying about colour coding and its affects on our lives on a day to day basis. Let’s talk about colour coding in Power BI and quickly get to more exciting stuff.

So… colour coding in Power BI, well, we could colour code from the day first that Power BI born, but, perhaps not in a way that I’m going to explain in this post. Conditional formatting is also around for a while now. In this post I show a technique that we can implement in Power BI to use a consistent colour coding across the whole report.

Here is a report without colour coding:

Power BI Report without Colour Coding
Power BI Report without Colour Coding

And now look the same report that is colour coded:

Colour Coded Power BI Report
Colour Coded Power BI Report

Let’s get into it.

Getting Started

In this technique we’ll follow the steps below:

  • We jump online using some awesome free colour palette websites to generate the colours we’d like to use in our reports
  • We copy the HEX values and paste into Power BI (via Enter Data)
  • We define a range of numbers to identify the ranges that our values will fall into. I personally use percentage, but it might be something else in your case
  • We then define some measures to pick a specific colour for the measures we want to colour code
Continue reading “Empower Your Story Telling Data Visualisation in Power BI with Colour Coding” →