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Category: Power BI

Power BI Query Diagnostics

Published 2020-02-17 by Kevin Feasel

Paul Turley has a video covering Power BI query performance:

This post demonstrates how the order of steps added to a query can make a big performance difference and drastically effect the number of steps generated by the designer. I’ll demonstrate how to use the new query Diagnostics tools to compare and understand query performance.

The Power Query Editor for Power BI simplifies data transformation processing by generating query steps for each action you perform in the query designer. This whiteboard diagram shows the high-level flow of information through a Power BI solution. Every query has a source (“SRC” in the diagram) followed by a connection. The query consists of a series of transformations (“XForm”) prior to populating a table in the data model.

Read on for a high-level explanation followed by a video which covers the Query Diagnostics feature.

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Storing Power BI Audit Logs in Blob Storage

Published 2020-02-17 by Kevin Feasel

Gilbert Quevauvilliers works around a built-in constraint with Power BI Audit Logs:

With the new Power BI Get-PowerBIActivityEvent I wanted to find a way where I could automate the entire process where it all runs in the cloud.

One of the current challenges with the Audit logs is that they only store 90 days, so if you want to do analysis for longer than 90 days the log files have to be stored somewhere. Why not use Azure Blob Storage?

Whilst these steps might appear to be rather technical if you follow them and you have access to an Azure Subscription you can do this too.

Gilbert warns us up-front that this will be a lengthy post and that is quite true. But if you need to hold those audit logs more than 90 days, this is a great way of doing so.

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Finding the Query Used in DirectQuery Mode

Published 2020-02-14 by Kevin Feasel

Kasper de Jonge shows us how we can find which query ran in DirectQuery mode to populate a Power BI data set:

When you are optimizing your DirectQuery model and you have done all the optimizations on the model already, you might want to run the queries generated by Power BI by your DBA. He then might be able to do some index tuning or even suggest some model changes. But how do you capture them? There are a few simple ways that I will describe here.

Read on for 3 1/2 such methods.

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Copying Measures between Power BI Datasets

Published 2020-02-13 by Kevin Feasel

Tomaz Kastrun walks us through copying measures between datasets and files in Power BI:

Measures in Power BI document are DAX based aggregations for slicing and dicing the tabular datasets using evaluate and filter context and and data relationships. Short hand, measures are DAX formulas stored in Power BI as part the dataset.

For showing how easy (once you know) is to copy measures between different dataset, I have created a sample Power BI with diamonds dataset (also available on Github).

I’d call the process convoluted. It does work, but it seems like Power BI should have an easier method.

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Removing Duplicates with Power Query

Published 2020-02-12 by Kevin Feasel

Matt Allington wants to remove duplicate records while retaining the last version of the record using Power Query:

Today I was helping a customer with a problem that seemed quite simple on the surface.  She had a data table containing historical customer sales orders (each customer has many orders on different dates).  The objective was to filter this table in Power Query and just load one record for each customer – the one that was the last order date.  To illustrate the problem more clearly, I have adapted the scenario using the Adventure Works database.

Click through for the demo, and also read the comments as there are a lot of interesting attempts to solve the problem there as well.

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Tips for Power BI Paginated Reports

Published 2020-02-12 by Kevin Feasel

Jonathan Jones has five tips to help you work with Power BI Paginated Reports:

Don’t use the Visual Designer, write your queries out first

As tempting as it can be to drop and drag fields and parameters into your dataset, I would not recommend it.  It makes it harder to repeatedly test, share the logic in the query, and see the results. Instead, write the script, whether it be in DAX or SQL.  Writing the queries is a faster process that gives you a lot more control over your queries.  If you don’t understand SQL or DAX to a proficient enough level, don’t panic, you could start the query with the visual designer and then convert it to the script.

When you’re running your DAX queries, don’t use the dataset query designer in the report builder, use DAX studio. DAX studio gives you the ability to efficiently query, format, and test DAX. As an experience it’s much faster and easier to show other people. If you are using SQL queries you could use SQL Server Management studio.

As a practice, when you’re trying to test the data, it’s important to get the data right in your queries before you place that data in your report.

Read on for the rest of the tips.

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Benford’s Law in Power BI

Published 2020-02-11 by Kevin Feasel

Imke Feldmann shows how you can build up a Benford distribution in DAX:

The green columns show how often each number should be the first digit in numbers that should follow the Benford-distribution. In black you’ll see the actual distribution of first digits within my table. Lastly, the red line shows the percentual absolute deviations between actual and Benford values.

In this example, there is a relatively high occurrence of numbers starting with 4 and 5. So this could be a sign for fraudulent manipulations.

In the example, eyeballing it says things look pretty good. It’s interesting to see just how many things fit a Benford distribution, including populations, budgets (when you have enough line items), expenses, etc. Not everything does, however—high and low temperatures tend not to, either in Fahrenheit or Celsius.

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Tenant Usage Monitoring with Power BI

Published 2020-02-11 by Kevin Feasel

Jeff Pries shows us the culmination of several blog posts’ worth of work:

Most of those posts (listed at the bottom of this page) are fairly long and technical — as, initially getting started using a program to read Power BI data via the API can be a bit much.

This post is going to be a bit different. Short and sweet. The payoff for all that hard work authenticating to Power BI, requesting data, downloading that data, and storing it in an easy to use SQL table.

With all of the hard work out of the way, its time to build a Power BI report to explore that great Activity Log usage data.

This is the payoff and it’s quite useful.

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Comparing Slicers and Filters in Power BI

Published 2020-02-11 by Kevin Feasel

Teo Lachev has a nice comparison of slicers versus filters in Power BI:

Besides the built-in cross-filtering and cross-highlighting among visuals, Power BI supports two explicit filtering options: slicers and filters. Which one to use? Traditionally, you would use a slicer when you want the user to easily see what’s filtered on the report page. But with the introduction of the new filter pane and slicer enhancements, the choice becomes more difficult. Let’s compare the two options:

Click through for a table of comparisons as well as some advice.

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Creating an Income Statement in Power BI

Published 2020-02-10 by Kevin Feasel

Joseph Yeates continues a series on financial statements in Power BI:

I had created a measure to populate the matrix visual. It uses =SWITCH() to return the YTD amount for the revenue and expense row headers and returns a subtotal for the net income header.

To finish building the income statement, I needed to add two more line items: retained income from the beginning and end of the year. I had already created the categories in the Power Query Editor, so I had to update the DAX statement to return logic for these lines.

Read on to see how to add these.

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