Edward Tufte recommended use of soft colors that do not tire the eyes. I’ve actually never read his books (yet), but a former boss of mine was a devout disciple and produced some beautifully soft color palettes.
Stephen Few, in “Show Me the Numbers,” reiterated Tufte’s color theories and recommended three sets of hues:
Light – for large shapes, e.g. bars
Medium – for small shapes, e.g. points
Dark/Bright – for calling attention to data
Click through for more including where you can get this Power BI theme. I’m not exactly the world’s biggest fan of the default palette so I’ll have to check this one out.
I have given many presentations and talks about Data Visualization, and still, I am amazed by how many visualizations I see which is not following the basic rules. In this article, I want to focus on table visual. A table is a visual that most of us are using it on many occasions, in fact, many users, like to see the data in table format. However, a table can be visualized in a way that is not readable. In this article, I’m showing you the most common style of a table which many report developers use, and then challenge it with a better style. The mystery is of course in conditional formatting. Like all my other articles, this article is demonstrating this technique in Power BI. If you like to learn more about Power BI, read Power BI book from Rookie to Rock Star.
Some of these formats are better than others, but you do have the power to do quite a bit with it in Power BI.
When I heard about custom data connectors for Power Query, I had assumed there would be a lot of work involved. While there is definitely quite a bit of work in implementing advanced features like query folding, creating your very first connector is simple.
So, first you need Visual studio installed and the Power Query SDK installed as well. Once you do that, you will see Power Query as an option when creating a new project. Visual studio will also have support for .pq or Power Query files.
Click through for an example of the process in action.
The Tooltips can display a string with multiple lines. This is useful for the DumpFilters measure that creates a new line for every column with a filter. You might wonder why the DumpFilters measure is required considering that Power BI can already display any filters and slicers affecting a visual. The reason is that the DumpFilters measure isolates the filters of a single cell and can show the effects of filters that are not visible in the standard visualization provided by Power BI.
This is interesting reading and a good way of sharing to users how they got to the current view of data.
Today, we’re going to talk about combining Stream Analytics with Azure Machine Learning Studio within Power BI. If you haven’t read the earlier posts in this series, Introduction, Getting Started with R Scripts, Clustering, Time Series Decomposition, Forecasting, Correlations, Custom R Visuals, R Scripts in Query Editor, Python, Azure Machine Learning Studio and Stream Analytics, they may provide some useful context. You can find the files from this post in our GitHub Repository. Let’s move on to the core of this post, Stream Analytics.
This post is going to build directly on what we created in the two previous posts, Azure Machine Learning Studio and Stream Analytics. As such, we recommend that you read them before proceeding.
Read on for the demo.
Today Gartner released the 2019 magic quadrant for Business Intelligence. As expected (by me at least), Microsoft is continuing its trail blazing and now has a clear lead over Tableau in both ability to execute and completeness of vision. I thought it would be interesting to see a trend over time for the last 5 years, as this is the time period that I have been a professional Power BI Consultant. I needed some way to extract the numerical data points from the images I had collected. This article shows you how to do that. Here is the final output – a scatter chart with a play axis in Power BI of course.
I was just commenting the other day about how somebody should do this and Matt went and did it.
First and most importantly, I updated the Power BI logo in the diagram to the latest version of the logo!
Secondly, I included Power BI Dataflows in the diagram tagged #6. Power BI Dataflows are used to ingest, transform, integrate, and enrich big data by defining data source connections, ETL logic, refresh schedules, and more. Data is stored as entities in the Common Data Model in Azure Data Lake Storage Gen2. Dataflow entities can be consumed as a data source in Power BI and by using Power BI Desktop. Read more about Dataflows here.
Click through for a full changelog and a link to download the architecture diagram and legend.
A violin plot is a nifty chart that shows both distribution and density of data. It’s essentially a box plot with a density plot on each side. Box plots are a common way to show variation in data, but their limitation is that you can’t see frequency of values. In other words, you can see statistics such as min, max, median, mean, or quartiles, but you can’t see the individual values nor how often they occurred.
Read on for a review of the custom visual available for violin plots, including areas where it does well and where it falls short at present.
But this function will not return any matches. I also tried out a (potentially) slower version using Table.SelectColumns(Types, each [Value] = x[Types]) – but still no match.
What I found particularly frustrating here was, that in some cases, these lookups or filters on type-columns worked.
That behavior seems odd to me. Imke shares a link from Microsoft which explains that the behavior occurs, but the why behind it eludes me.
As per Microsoft docs:
“This feature lets you create a custom group of slicers to keep synchronized. A default name is provided, but you can use any name you prefer.
The group name provides additional flexibility with slicers. You can create separate groups to sync slicers that use the same field, or put slicers that use different fields into the same group.”
First, let’s look at creating groups to sync slicers that use the same field. The use case Syncing within a page, we can easily use the group functionality to do this.
Click through for a few demos of increasing complexity.