Welcome to a new podcast from PowerBI.tips, Explicit Measures. We aim to discuss relevant topics and thoughts around Power BI. Join us Tuesdays and Thursdays at 7:30 am CST (-6 UTC) on our YouTube Channel and subscribe on Spotify Podcasts.
Answering the Why
For most of you who casually visit or frequently visit PowerBI.tips, we deal with many tools, features, languages, and situations in modeling, visualizing, and distributing our data and reports. We are the Power BI Power Users, capable and responsible for building complex solutions. We have to be continually acquiring new skills, and improving on our processes & standards.
Additionally there are so many resources available out in the Power BI Community. So many amazing champions and industry leaders who share their knowledge and expertise on how to build faster, better, and more reliable reports. As a developer we increasingly tasked with, How to audit your data? or how to create complex calculations? We learn best practices and better workflows to implement in our daily tasks.
One aspect of what we do that is not easily discovered in the community, the why of what we do. The why of building reports is universal across all Power BI Pros. As professional BI developers we know the how. If we don’t know the how, we learn the how. This begs the question about the why? Why this particular feature, tool, or product integrate with my organization or my team? Why would my users need this? What does this mean for me?
The why is the question around every BI pro’s water cooler. You may ask this yourself. Possibly sitting at your desk after a meeting, or as you engage with the Power BI community, or User Group. No matter how you get to it, we all face common questions. Eventually all of us will need to ask these types of questions.
Today this is why I am excited to introduce the new Explicit Measures Podcast, available every Tuesday and Thursday live at 7:30am CST.
The Background of the Podcast
Being a Power BI Author
I have been part of the Power BI World since it was “Power BI Designer”. As soon as I was able to download the first application version of Power BI Designer, I was hooked. I felt it was intuitive, complex enough, and just worked. At the time, our organization was vetting new BI platforms. I strongly made the push that we adopt this new tool.
I decided to put all my eggs in the Power BI basket. Believing this tool could easily be widely adopted as it’s part of Office 365, everyone has Office 365. The barrier to entry was low, and we already have strong community. A community of Excel gurus, Power Query and Power Pivot experts.
Over the coming months, we moved Excel files to Power BI, and eventually became a Power BI shop. I soaked up any and all information and resources on how to create DAX measures. Learning what the heck Filter and Row context where. Then figuring out how to create my own function in Power Query. This process was love at first sight. It felt that I was bringing advanced data solutions to my users. I was able to create models and create relationships that otherwise would not have been able to exist. Created tables that finally bridged so many gaps in the data.
I would jump in my chair when a new Desktop version was released. Any new feature that caught my eye would immediately be something I wanted to integrate into my reports. Drill Through (I think at the first Data Summit before being MBAS?) feature was a game-changer to me.
The problem was what I thought was a game changer, which they are. This same excitement did not translate among colleagues who did not focus on data or felt overwhelmed by data. Many of our old Reports were built in SSRS, and users liked them for what they provided.
Excitement vs. Expectations
Drill through, interactive visuals, and other complex features that were in these Power BI reports became overwhelming to users. Not only that, but any data analyst was also now working in Power BI. They were building their own reports, with their own filters, and their own business logic.
What arose from these implications was the matter of users losing trust in the reports. They lost trust in the data they needed to rely on. A department with one report would complain about a certain KPI being too low, while the defending department claimed their report was provided a more adequate number. Users did not know what reports to use, much less how to use drill through. They wanted what would provide them the value they needed.
This brought me to an epiphany of sorts, or multiple over numerous situations. Not only about the importance of governance and adoption in Power BI, but at the end of the day, why do we do what we do? Why are we in this space, and what are we ultimately judged and measured on showing success and real impact at where we work?
Focusing on the Why
This brings us back to the Power BI Water Cooler. How many of us have delt with these sort of situations, problems, and trying to find a solution? I would put good money on the majority of us who have been working with Power BI for a while have gone through this type of arc.
In conversations with other User Group Leaders, the community, and other Microsoft MVPs. I have learned time and time again this is not a siloed story. What can really separate a Power BI Tech vs. a Power BI Pro is the ability to think of alternative solutions. What is the ultimate impact of any feature, product, or visual on the most important audience, the consumer.
We must think this way. We must be able to process all of the new capabilities that come out at rapid speed. Then understand who our consumers are. Finally, understand of not just Power BI but the data, and where can we further drive more and more trust into the data.
Being Explicitly Measured
I want all of you whom this article may hit close to home to join us in this ever-going discussion. Having the pleasure of knowing Mike and Seth of this site has shown this need is so prevalent. We want to bring to the surface these questions, topics, and discussions. There is more than one way to define a measure, but the importance is that you start with some definition.
That is truly where the name of the podcast, Explicit Measures, comes from. Being able to start with a use case (take the technical situation of defining a measure), understand what is available to you (the functions), and what is best to apply (FILTER inside a CALCULATE, ALL or ALLSELECTED?).
The Explicit Measure Podcast is meant to be first entertaining for users. We all need an outlet for some of the frustrations we feel by end users, and being with fellow users who understand the pain helps the feeling you are not alone!
The heart is in the ability for us to debate, argue, and most of all inspire. Find solutions, figure out what impacts us and where can we go from here.
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