A few years ago, on February 14th, 2013, I fell head over heels onto a rocket ship that kicks just as much, well it kicks more ass than Tyler Durden on his best day. Valentine’s Day coincidence? Maybe I’ll get…
Your First Co-Development Project P3 has tried many different flavors of our brand of “consulting” through the years, but co-development projects that combine real projects with coaching and knowledge transfer have turned out to have been the sweet spot in…
Welcome to the latest PowerPivotPro Coffee Talk, where members of the community discuss various topics related to Power BI, Power Pivot, and Analytics/BI in general. These conversations take place during the week on a Slack channel, and are then lightly…
Hi folks. Today we are fortunate to have a guest post from David Hager. He explains a technique for counting how many new customers are acquired or “seen” each day. (I’m going to think about whether this has web site traffic analysis uses as well – New Visitor vs. Returning Visitor sort of stuff).
Information vital to any company is being able to identify customer patterns. Counting how many new customers per day a company acquires is perhaps the most important data that can be obtained. The following model will show how this can be done with DAX measures in PowerPivot. For comparison, two other measures are included in the Pivot Table (shown in Figure 1).
Note that COUNT(Table1[CustomerID]) would return the same result.
This measure returns the number of unique customers.
This formula shows the real power of DAX. The first part of the formula (highlighted in green) returns the running total of the DistinctCustomersPerDay measure. The second part of the formula (highlighted in yellow) returns the running total of the DistinctCustomersPerDay measure up to the previous day of the pivot table row context. The difference affords the number of new customers per day.
***UPDATE – FULL: Wave one filled up fast, no need for 48 hours. We actually went over 100 during the night and hit about 130. We’re letting all of those in, but are taking down the signup form now.
Stay tuned for news about Wave Two
If Ebenezer Scrooge Were Alive Today, He’d Use PowerPivot. And He’d Love This Post. (Believe it or not this is an original image I commissioned ten years ago)
Taking my “High Priest” Role VERY Seriously
There are a few themes that I just keep hammering on, month after month. Most of those revolve around the stunning new future opening up for Excel Pros. I believe every thing I say about that stuff. It is REAL.
One of the biggest and most transformational changes is this: taking your workbooks to the web. Workbooks were being emailed around back when Roxette topped the worldwide music charts. PowerPivot workbooks published to a server are a very, VERY different experience, one that inspires MUCH more respect from the person consuming them.
Short Version: Free Forever for Lighter Workloads
This week, Pivotstream is launching something that I’ve been dreaming about for a long time: a way for you (yes YOU, dear reader) to harness the power of PowerPivot server (publishing workbooks as interactive web apps)… for free.
Not a trial. This is more of a Dropbox-style model where lighter usage is completely free, and you only pay if you want more capacity. I want to remove any barriers I can so that you can experience what I’m talking about (without bankrupting my company of course), and I think we’ve figured out how to do that. But before I get into details, let me show you something.
Just Add Upload
Thanks to a recent focus group I recruited here on the blog, I learned that many people expect there to be some sort of intensive conversion process – it seems like you would need to put a lot of work into a workbook before it becomes an interactive web application like the ones on our demo site.
So I recorded a video showing that it’s much, MUCH simpler than that. Just upload
Upload and Share – Short Video Illustrating an Even Shorter Process (I recommend watching in HD and Fullscreen)
Benefits to Excel Pro
I didn’t have time to cover this in such a short video, so here’s a quick table comparing the old way to the new way, through the eyes of you, the Excel Pro:
My First Real Experiment with Power View – Built From a PowerPivot V2 XLSX!
(Running on our New V2 Cloud PowerPivot Platform)
Lots of Work Pays Off
The #1 question I hear every day is “when will Pivotstream offer support for V2 on their cloud platform?” And in fact, that’s maybe the #1 question that I ask of the team every day, too.
There’s a lot of demand for it, given all the new bells and whistles in the V2 release. But we’re no longer a fledgling little operation – we can’t just upgrade everyone overnight. Actually, we could, but that would be irresponsible – we have to make sure none of our customers get burned in the process, and huge software releases like V2 have a tendency to be… finicky. If we upgrade everyone and things start breaking, saying “it’s Microsoft’s fault” is not an answer – we have to hold ourselves to a higher bar.
So our V2 cloud platform is a completely separate and parallel investment – new hardware, new domains, new base URL’s, etc. A lot of time and money, in other words. So if you’ve been wondering “what the heck are they waiting for,” now you know.
After completing the Part 3 extension of Rob’s Dynamic TopN Reports via Slicers, Part 2 post, I did not plan on a forth installment. However, I did plan to write about creating dot plot PivotCharts sometime in the future. Later, it occurred to me that the TopN reports model provided the perfect foundation upon which to create dot plot charts.
The dot plot is not a standard chart type in Excel, so most users haven’t heard of, let alone used one. The dot plot is an alternative to a horizontal bar chart, and there are many situations where it is a better fit for analysis. For a good introduction to dot plots, see this excellent article by data visualization expert, Naomi Robbins.
The following summarizes some of the potential advantages of the dot plot over a bar chart:
When there are a lot of category items on a chart, a bar chart can look cluttered. Because a dot plot uses less “ink” to represent the same data, the resulting chart tends to be less cluttered.
The dot plot is often better than a stacked bar chart. The values in a stacked bar chart can be hard to compare because only the bottom bars have a common baseline.
Depending on how the dot plot chart is organized, you can gain better insights than using a clustered bar chart (see example in Naomi’s article).
Since the absolute length of a bar chart encodes its value, the value axis must start at zero. If the values in the chart are all a distance from zero, you can’t make good use of interval values on the value axis. On the other hand, the dot plot values are judged by position along the axis – length is not involved. Therefore, you can have more optimal intervals on the value axis.
FIgure 1 shows dot plot PivotCharts based on the data used in Part 3.
Figure 1 – Dot plot PivotCharts (Click figure for an expanded view)
After Rob posted Dynamic TopN Reports Using PowerPivot2!, I downloaded the workbook from the provided link to examine how his “tricks” were done. Shortly thereafter, I sent a message to Rob complementing the techniques he used, and mentioning the potential for using the techniques in other scenarios – especially those that include dynamic charts. I didn’t realize that I was setting myself up, because Rob asked if I’d be willing to write a post detailing one of these scenarios. For the sake of continuity, it makes sense to treat the scenario that I will be discussing as an extension of Dynamic TopN Reports via Slicers, Part 2. You should have thoroughly read and understood that post before you continue here.
The additions that I have made to Rob’s TopN reports are as follows:
Created BottomN measures for Customers
Created TopN/BottomN measures for Products
Added a Year-Month slicer
Created TopN/BottomN charts for customers and products that react to slicer selections for TopN, By (selected measure), and Year-Month range.
The final result of these efforts is shown in Figure 1.
Figure 1 – TopNBottomN charts (Click figure for a wider view)