In today’s post, we will continue to review the claims against Power BI (as was published by Tableau here), and demystify three more claims.
This is the second part of a new series for Tableau pros, or BI teams, who consider extending their BI portfolio, and start their Power BI journey. Read part 1 here.
Disclaimer: This isn’t going to be a typical comparison between two different solutions. I am not objective here. In a different lifetime, I might have become a great advocate for the other solution. After all, it has great visualizations, and a fantastic community of professionals and fans. You might also argue (especially if you are a fan of the other product), that I have no real claim to share my thoughts here. After all, I have never used the other product.
Nevertheless, if you are a fan of the other solution (and by now may be a bit angry that this blog post was shared with you, by someone from the other side), I think you should read this blog post, and the series which will follow. I am not going to convince you to stop using the other product. But it’s definitely time for you to start using this new emerging product. In the next 10 years, it will conquer the world. It has already started. And you cannot afford to stay behind.
Demystifying Power BI misconceptions
Missing Outliers in Scatter Charts – The 1st Way Power BI Falls Short – Or Not
As discussed in the last post here, Tableau claims that Power BI’s first shortcoming is that it misses outliers in scatter charts. In the last post, we demonstrated how the outliers can be detected, and pointed you to additional custom visuals that specialize in outlier detection.
As a follow up for part 1, there are two interesting points to consider:
- Does it make sense by Tableau to select this point as the first Power BI shortcoming? Dear Tableau marketing team, you may consider sorting the shortcomings by severity, and do it in descending order.
- Power BI team is seriously addressing any identified gap. In Power BI Desktop (June update) the High Density Sampling was announced here. The team updated the sampling algorithm for line and area charts. “The new algorithm will better preserve the shape of your data and while also surfacing outliers”. The team will “continue to invest in this area and improve other visuals as well”.
DAX – The 2nd Way Power BI Falls Short – Or Not
According to Tableau, many of the simplest calculations in Power BI require you to learn DAX, which make it difficult to quickly answer easy questions. Here is a screenshot from their website:
While DAX does require you to embark on a journey of discoveries (Start here and move your way to here, here and here), a massively growing community of Excel and SQL Server practitioner can testify that DAX has transformed their careers. Nevertheless, quick analysis is crucial in any BI tool, especially for common questions. To answer this need, Microsoft released the Quick Measures on April, 2017. With Quick Measures (which is still in preview), you can perform a wide range of common calculations without the need to learn DAX.
To keep the pace of innovation, Microsoft announced the Quick Measures Gallery – A community forum for Power BI practitioners, who can now share their most useful DAX calculations, and vote for the best measures. Microsoft intends to evaluate the most favorable measures, and consider them as candidates for the Quick Measures dialog above.
You can show the percent of grand total, column total or row total without using DAX.
Limited Trends and No Forecasting – The 3rd Way Power BI Falls Short – Or Not
According to Tableau, Power BI has limited trend line capabilities and no forecasting. Here is a screenshot from their website:
Till June update, you could implement trend lines (here), and easily apply the Forecasting Power BI R custom visual (Without the need to learn R).
Last week, Microsoft made a significant improvement in this area, and announced the new Analytics pane where you can create dynamic reference lines, and forecasting (in addition to the previously supported trend line).
Here are the supported reference lines:
- X-Axis constant line
- Y-Axis constant line
- Min line
- Max line
- Average line
- Median line
- Percentile line
By expanding the Forecast section of the Analytics pane, you can specify multiple inputs to modify the forecast, such as the Forecast length, the Confidence interval, and others. The following screenshot shows a basic line visual with forecasting applied.
You can’t compare several categories – The 4th Way Power BI Falls Short – Or Not
According to Tableau, you can’t compare several categories in Power BI. Here is a screenshot from their website:
The statement above is not 100% accurate. You can easily compare multiple categories in Power BI. Moreover, in the latest Power BI Desktop (June update) Microsoft released the new Data Bars, which can compare between many categories in the new table and matrix visuals. Here is a real example:
Stay tuned for the next blog post to learn how Power BI addresses the last four supposedly shortcomings.
Curious to learn more, here is a preview of the next 4 ways where, according to Tableau, Power BI falls short:
Can’t customize or format tooltip (popup) content – The 5th Way Power BI Falls Short – Or Not
According to Tableau, you can’t customize the tooltips, and as a result, you may not see all of the details in your data. Here is a screenshot from their website:
No offline work – The 6th Way Power BI Falls Short – Or Not
According to Tableau, you can’t download the report from the web for offline editing. Here is a screenshot from their website (Seriously? Didn’t you know you can download the PBIX file from Power BI service?).
Storytelling – The 7th Way Power BI Falls Short – Or Not
According to Tableau, you can’t tell a narrative with the data in Power BI, leaving you with too many annotations and labels. Here is a screenshot from their website:
Clue: Storytelling in Power BI is alive and kicking, and in the next 3 months, Microsoft will release a series of game changing experiences. More details in the next blog post.
You can’t ask What-if Questions – The 8th Way Power BI Falls Short – Or Not
According to Tableau, you can’t input data into Power BI, so you can’t answer “what-if” questions. Here is a screenshot from their website:
Clue: What-Ifs are supported today in DAX, and in 3 months, Microsoft will release improved experiences.
Starting to see the pattern here?
In one way or another, most of the gaps above were addressed by Power BI. But recently, Microsoft has aggressively nailed down the gaps in the last two updates. As we’ll see in the next blog post, with the new announcements in Microsoft Data Insights Summit, the gaps will become obsolete in the next three months.
In the next two blog posts we will gradually transition from the “defense” to the “offense”, and will share the unique value of Power BI.
Update: To continue reading the next episode in this series, click here.