All posts by Dustin Ryan

Dustin is a Senior Business Intelligence Consultant with Pragmatic Works. You can find Dustin blogging and speaking at events like SQL Saturday, Code Camp, and SQL Rally. Follow Dustin on Twitter @SQLDusty.

Three Best Practices for Power BI

Since the release of Power BI Desktop this past week, I’ve been really spending my extra time digging into the application focusing on learning and experimenting as much as I can. When my wife has been watching Law and Order: SVU reruns at night after the rug rats are in bed, I’ve been right there next to her designing Power BI dashboards like the total data nerd that I am. When my kids have been taking their naps during the weekend, I’ve been writing calculations in the model for my test dashboards. Or when I’ve been riding in the car back and forth to work I’ve been thinking of new things to do with Power BI Desktop.

Since I’ve been spending a decent amount of time with Power BI Desktop, I thought I’d take a moment to share three things to know and remember when designing your Power BI models and dashboards that I think will help you make the most of this tool and be effective at providing the data your business needs to succeed.

1. Optimize your Power BI Semantic Model

It probably hasn’t taken you long to figure this one out if you’ve built Power Pivot/Tabular models or at least it won’t when you do start developing Power BI dashboards. The visualizations in Power BI and Power View are heavily meta-data driven which means that column names, table or query names, formatting and more are surfaced to the user in the dashboard. So if you using a really whacky naming convention in your data warehouse for your tables like “dim_Product_scd2_v2” and the column names aren’t much better, these naming conventions are going to be shown to the users in the report visualizations and field list.

For example, take a look at the following report.

Power BI Dashboard without formatting

Notice anything wonky about it? Check the field names, report titles and number formatting. Not very pretty, is it? Now take a look at this report.

Power BI Dashboard with formatting

See the difference a little cleaned up metadata makes? All I did was spend a few minutes giving the fields user-friendly name and formatting the data types. This obviously makes a huge difference in the way the dashboard appears to the users. By the way, I should get into the movie production business. ;)

My point is that the names of columns, formatting, data types, data categories and relationships are all super important to creating clean, meaningful and user friendly dashboards. The importance of a well-defined semantic model cannot be understated in my opinion. A good rule of thumb is to spend 80% to 90% of your time on the data model (besides, designing the reports is the easy part).

I’d also like the mention the importance of the relationships between the objects in the semantic model. Chance are you will have a small group of power users that will want to design their own dashboards to meet their job’s requirements and that’s one of the beauties of Power BI. But when users began developing reports, they may query your model in unexpected ways that will generate unexpected behaviors and results. I only want to mention this because the relationships between the objects in the model will impact the results your users will see in their reports. Double check your relationships and ensure that they are correct, especially after you add new objects to the model since the Power BI Desktop will sometimes make an incorrect guess at creating the relationship.

2. Choose the Right Visualizations

The best dashboards are those that tell a clear story within seconds. Your data should tell a story that is easy to read and can communicate the tale of the data to the users without a lot of extra work on their part. If your users have to look at the report for a long time in an attempt to decipher the visualizations plastered across their screen, chances are they won’t want to use your dashboard.

Let’s look at two different charts that I think will illustrate my point on the importance of choosing the right visualization for the story. The chart below shows a comparison of Domestic Sales and International Sales for different movie genres. If the purpose of this chart is to determine from which market most of the money comes from for the various film genres, then this chart isn’t doing that great of a job because we can’t clearly see the difference between the markets for Westerns.

Power BI line chart

Is there a better way to tell the data’s story? What about the pie/donut chart?

Power BI donut chart

Goodness, no. Stay away from pie and donut charts. The problem with pie/donut charts is that even with only a few categories it can be very difficult to compare the slices in the pie. And if the purpose of our dashboard is for the users to quickly gain insights into the successes and failures of the business, I recommend you stay away from the pie/donut charts.

Power BI clustered bar chart

Now that’s what I’m talking about! With a clustered bar chart, we can clearly see from which markets most of the money comes from the different genres. This is a much better visualization choice for the data. We don’t have to stare and squint in order to determine the differences between the bars.

Visualization choice is critical with designing an effective and useful dashboard, so always make sure you choose the best visualization for the job.

3. Remember the User!

We as developers can oftentimes find ourselves lost in the minutia of data processing times, ETL performance, writing code, documenting the solution and all the other things that go along with designing and building a business intelligence solution. In the midst of all that awesome and glorious development work, it can be easy to forget that the whole purpose of this solution is to make the user’s job easier, faster, better, etc.

I only mention this because too many times I’ve encountered solutions that did not make the user’s job easier. Users are crafty and resourceful people. They’re (mostly) good at their job and will find a way to do their job without having to use your crappy dashboards and reports that are confusing and difficult to use. And once you start down the path of having your users work around your solution instead of with your solution, your solution has failed because at that point its not a solution; It’s an impediment.

Meet with the users as frequently as necessary to constantly gather feedback. During the requirements gathering phase its important to ask lots of questions especially if you’re unfamiliar with the data. And once its time to start designing reports, you may meet with the users even as frequently as daily since this will be the user’s primary way to interact with your solution. I’ve been on projects where my team and I worked in a conference room with a few power users. This was excellent as we were able to get immediate feedback on any reports developed and make the required changes as desired.

Wrap Up

So in a nutshell, here are my three best practices for designing and building a killer Power BI reporting solution:

  1. Optimize the data-model by doing the following:
    1. Set data types correctly
    2. Apply user-friendly formatting to the data including explicit measures.
    3. Rename fields, measures, and tables with user-friendly naming conventions.
    4. Validate relationships between tables are created correctly.
  2. Use the right visualization that communicates the story of the data as clearly as possible.
  3. Remember the user and their experience with your solution! If the user likes to use your solution then its a success!

 

More Resources

Here’s a few more Power BI related resources you may find useful:

Check out the new visualization types in the latest release of Power BI

Learn about Power BI Desktop in this video walkthrough
Learn Power BI Desktop with Dustin Ryan

Feedback?

So what do you think? What best practices did I leave out that you thought I should have included in this list? Leave a comment down below and let me know! And as always, thanks for reading. :)

Power BI and Big Data

If you’re worked in the wide and diverse field of information technology for almost any amount of time, it probably hasn’t taken you long to discover that the one thing constant about IT is that the technologies and strategies involved change faster than you can learn them. And if you work in business intelligence like I do, you don’t have to look very far at all to see change. The Microsoft Power BI team rolls out a software update every month! If I want to stay learned up on the technology, I have to really be on top of things.

About ten years ago when Hadoop was first being developed at Yahoo, Continue reading Power BI and Big Data

New Visualization Types in Power BI Desktop

In the July 2015 update for Power BI Desktop there were a load of improvements to the tool including new data sources, new transformations, direct querying of SSAS Tabular Models, new Data and Relationship view, publishing directly to your Power BI site and some new visualization types.

Dashboard report built with Power BI Desktop

The new visualization types added to Power BI Desktop are the Waterfall chart, Area chart, Donut chart Continue reading New Visualization Types in Power BI Desktop

#MDXMonday: Previous Year Month to Date Calculation

I recently had a client give us a call asking for helping creating a calculation in her cube to show the month to date value for the previous year. Here’s the basics of the calculation I created.

View last week’s #MDXMonday –> Calculating Daily Average Sales

This calculation involve two parts. First we must create a calculation that figures the month to date value of the measure in question. To do this I used the MTD function along with Continue reading #MDXMonday: Previous Year Month to Date Calculation

Introduction to Power BI Desktop Video Walkthrough

Last night I finished editing and posting my video walkthrough of Microsoft’s new Power BI Desktop tool. This tool is awesome! If you’re looking for an end to end analytics tool that will allow you to consume all types of data sources, mash it up, and then report on it in one single place, this tool can do that.

So give my video walkthrough a watch to get ramped up on Power BI Desktop and leave a comment down below if you enjoyed and learned something from the video!

Power BI Desktop: My First Run Through

If PowerPivot, Power Query, and Power View had a baby (don’t ask how) that baby would be called Power BI Desktop Designer. Yesterday the Power BI Desktop Designer was released for general availability, which I promptly downloaded last night at 11:30 PM EST and started playing with. Even as my wife turned out the light and begged me to go to sleep, I persisted! I was too excited. So here’s my first run through (I call it run through because it was late and I didn’t spend a ton of time looking at every little thing).

–> Scroll down to see some of the dashboards I created. <–

*Update: James Phillips, a VP at Microsoft, has corrected me in the comments on the name of Power BI Desktop. After GA, the tool is no longer called Power BI Desktop Designer. From henceforth it shall be known as Power BI Desktop. Now please ignore all the references to “Desktop Designer”. :)

**Update: As I continue to play with the Power BI Designer, I’ll post any new dashboards I create at the bottom here while learning the tool

Download Power BI Desktop

Ok first things first. Download the Power BI Desktop Designer so you can start playing!

http://www.microsoft.com/en-us/download/details.aspx?id=45331

Installing it is pretty straight forward so I’ll spare you the details.

Get Data with Power BI Desktop

The first thing I did after installing the Power BI Desktop Designer was Continue reading Power BI Desktop: My First Run Through

My Top Four Books for the MS Business Intelligence Professional

As a Business Intelligence Consultant, I do a decent amount of speaking, interacting with the community, and have written and contributed on a few SQL Server books. A question I’m often asked is if I can recommend any good books which brings me to this blog post. I wanted to make you aware of four books for learning data warehousing and  other MS BI technologies that I’ve found incredibly helpful over the years I’ve spent designing and implementing enterprise data warehouse and business intelligence solutions. Continue reading My Top Four Books for the MS Business Intelligence Professional