Power BI offers many advanced functions for data analytics but you do not need to be an expert to use it.
In fact, it can be very useful, regardless of your knowledge of data analysis – which is what it should be! Here are 5 tips on how to make the most of Power BI reports.
Power BI is a great tool for data visualization and (some) data transformation, no doubt about it. Over the last years of its development, it gained many great features and capabilities.
There are also many resources available on the Internet if you’re looking for training materials (which is not what you’ll find here). I assume you have touched upon this technology at least a bit. At the same time, you’re probably not a hardcore analyst, as you would most likely know all these tips already.
This article will not tell you how to do all the things you possibly could with Power BI. In fact, you should try it for yourself, it’s very intuitive and allows you to build very advanced visualizations.
Once you stumble across a challenge, you should look up answers online on how to approach it. Or, you can check out our data visualization pack.
That’s exactly what we did here at Predica – we’ve built a companywide analytical reporting tool that anyone in the company can use without extensive training. Not to be modest, I would even say it took us very little time to achieve it.
However, we have already invested much effort into building and maintaining proper data sources. Therefore, I’d like to share some experiences we’ve had. I will also share little hints we use in creating reports both for us and for our customers.
Following the idea of delivering a message… There is an increasing number of visualizations available in Power BI which you can get from AppSource. Some of them are pretty complex. They can show you the relations between data elements in an unordinary way that can make sense… quite rarely (for example, if you’re a hardcore analyst).
Selecting the right chart for your data
For most of us ‘ordinary people’ – and I’m saying, probably 98% of us – simple means better, easier, clearer, …..er [put here whatever you think suits]. So, focus on simplicity!
In most cases, a (boring) bar or line chart will surely suffice. Also, don’t fear the old-school and ‘ugly’ tables – they are still the best way to present raw data, which is sometimes all you really need (and what you keep using Excel for!).
For example, I try to avoid pie charts and treemaps for a very simple reason – you cannot see the difference between pie fields that have similar values.
Let’s try to report the sales volume per region – try telling whether red or orange is bigger or by how much they differ:
Isn’t this clearer?
One of the coolest features of Power BI is its cross-filtering capability. It means that once you have two charts with connected data next to each other, when you click on an element on one, the other will be filtered based on what you clicked.
This greatly helps with the data comparison, kind-of-visual drill-downs, and simple analysis.
Using filters in Power BI
But what might not be so obvious at first sight, is that you can actually use three ways of filtering and connecting data to make your analysis experience better and easier.
Let’s consider the project management example. You may be interested in seeing the time reported by people (top bar in the below example) and the time reported each month (the bottom bar). There you can see the different behaviors the interactions provide.
No filtering happens between elements. Use it if you want to display data as it is so that it’s not affected by users’ behavior. In the example – clicking on the bar in the top chart does not influence data displayed on the bottom:
The filtered value is displayed in the context of the total. Use it when you want to show how much of the total the selected element forms. In the example – clicking on the bar in the top chart fades out the bottom chart. Only the part of the bar which is applicable to the clicked element remains highlighted:
Displaying the actual filtered value. Use it when you want to see what actually hides behind the selected element. Here you are interested in the detailed data and not its relation to the total. In the example – clicking on a bar in the top chart filters out the bottom one and leaves only the data applicable to the clicked element:
So, depending on the context in which you are viewing your data, it may have a significant difference on which relationship you select.
Additionally, when there’s a lot of data elements, it might greatly influence the ease of use of the report, especially for not advanced users (who we usually create such tools for).
Find more info about creating interactions between visualizations here.
It’s the most basic concept of data visualization, yet you might still be surprised by how many filtering possibilities there are in Power BI reports. Here are 5 obvious ones.
Again, let’s consider the project management example. You can think of having a multiple page report with pages giving you an overview of hours (like in the interactions example) or details of time reported under particular tasks (as in the above example).
So, if you use in-canvas filters, you need to select the project you are interested in on each page individually. However, when you use report level filters, the project is still selected when you browse through different pages. Now, imagine having a report with 7 or more pages… try it yourself and you will see how much sense it makes.
Hierarchies are a great way of showing data analytics on various levels of granularity using the same visualizations. For example, in a project management domain, a program manager may be interested in project(s) progress and time reported per month, whereas a project manager could be interested in a weekly level to look into what is happening more closely.
Obviously, you can create different reports for each of them. However, you will then end up managing and supporting a large number of such cases. Alternatively, you can be clever and design a report in a way that can be used by both. And this is where hierarchies come in handy.
Using hierarchies in Power BI
Once you have some, just notice the small arrows that appeared in the corner of the chart which you can use to go up and down the hierarchy levels:
The same visualization and report is used to achieve different perspective views.
Since it’s easy and fast to create reports in Power BI, you can be tempted to create many of them just because you can. But think of the poor users who will be using these reports and how they can get confused when they get tons of reports or pages showing similar things…
Once you let people into a tool like Power BI, the effect could easily end up being a Picasso-like analytical painting with many colors but really not much value to it. In a matter of seconds, you can produce any number of beautiful charts showing any number of data pieces like a well-operated assembly line.
Yet, Power BI reporting canvas is like PowerPoint slide – no scrolling or pagination can make you feel… limited. But that’s the whole point! The time you spend in Power BI should be spent on trying to fit and visualize the information in that space. It should be clear and easy to digest by potential users at a first sight.
It is especially important when you consider that Power BI has two display areas:
Consider this sales opportunities example from Microsoft:
Luckily, this is only the demo dashboard presenting product capabilities rather than anything of real use. This is a bad practice example as all tiles in this dashboard show pretty much the same data (opportunity count and revenue), just from a different angle. This makes it more analytical than the status view. Consider how this can be simplified to put focus only on the important things – the actual opportunities’ number and volume:
Not only can you see it better, but you also have more space to add other (meaningful!) things. If you want to know more about the data displayed, you just need to click on any of the tiles to get the report where you can see all the data from the original dashboard:
So, the rule of the thumb is: include less, but only the meaningful stuff. Remember that the information you want the user to get is the most important. It’s not about the overwhelming number of data views in all possible dimensions.
It should be clear at first sight whether there is a problem or not, whether you need to investigate further or have a peaceful moment to grab a cup of coffee.
The concepts presented above are very basic advice that you can use when creating reports that should be simple and easily understood by regular users. I collected them here as they are also built on our experiences from designing analytical reports for our company.
They are now successfully used by people across project management, finance and development practices. All thanks to simplicity, focus on the users’ needs and spending more effort on figuring out what should be the most efficient way to tackle the particular piece of data and then create the report.
Don’t forget to check out the Power BI blog to be up-to-date with new features and releases.
Curious to see some more examples? Check out our customer stories where you can see how clear and customized reports make work easier for people across industries:
And remember: it’s easy to create Power BI report, but it’s a little harder to create a meaningful report. Contact us to make sure you only have the best ones!
Sales forecasting is the process of estimating future sales based on all available data on past and current transactions...
In any business, it's important to reduce development times, save money, and predict demand more accurately. By using da...